Index

_

__eq__() (nannyml.drift.univariate.methods.Method method) (nannyml.performance_calculation.metrics.base.Metric method) (nannyml.performance_estimation.confidence_based.metrics.Metric method) (nannyml.performance_estimation.direct_loss_estimation.metrics.Metric method) __len__() (nannyml.chunk.Chunk method) __repr__() (nannyml.chunk.Chunk method) __str__() (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationAccuracy method) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationAP method) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationAUROC method) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationBusinessValue method) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationConfusionMatrix method) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationF1 method) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationPrecision method) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationRecall method) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationSpecificity method) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationAccuracy method) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationAP method) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationAUROC method) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationBusinessValue method) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationConfusionMatrix method) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationF1 method) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationPrecision method) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationRecall method) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationSpecificity method) (nannyml.performance_calculation.metrics.regression.MAE method) (nannyml.performance_calculation.metrics.regression.MAPE method) (nannyml.performance_calculation.metrics.regression.MSE method) (nannyml.performance_calculation.metrics.regression.MSLE method) (nannyml.performance_calculation.metrics.regression.RMSE method) (nannyml.performance_calculation.metrics.regression.RMSLE method) (nannyml.performance_estimation.direct_loss_estimation.dle.DLE method) (nannyml.performance_estimation.direct_loss_estimation.metrics.Metric method)

A

Abstract1DResult (class in nannyml.base) Abstract2DResult (class in nannyml.base) AbstractCalculator (class in nannyml.base) AbstractEstimator (class in nannyml.base) AbstractEstimatorResult (class in nannyml.base) AbstractResult (class in nannyml.base) accuracy_sampling_error() (in module nannyml.sampling_error.binary_classification) (in module nannyml.sampling_error.multiclass_classification) accuracy_sampling_error_components() (in module nannyml.sampling_error.binary_classification) (in module nannyml.sampling_error.multiclass_classification) add() (nannyml.plots.components.hover.Hover method) add_alert() (nannyml.plots.components.figure.Figure method) add_artificial_endpoint() (in module nannyml.plots.util) add_confidence_band() (nannyml.plots.components.figure.Figure method) add_metric() (nannyml.plots.components.figure.Figure method) add_period_separator() (nannyml.plots.components.figure.Figure method) add_threshold() (nannyml.plots.components.figure.Figure method) Alert alert() (in module nannyml.plots.components.joy_plot) (in module nannyml.plots.components.stacked_bar_plot) (in module nannyml.plots.components.step_plot) (nannyml.drift.univariate.methods.Chi2Statistic method) (nannyml.drift.univariate.methods.Method method) (nannyml.performance_calculation.metrics.base.Metric method) (nannyml.performance_estimation.confidence_based.metrics.Metric method) (nannyml.performance_estimation.direct_loss_estimation.metrics.Metric method)

AlertCountRanker (class in nannyml.drift.ranker) alerts() (nannyml.base.AbstractResult method) analysis_data (nannyml.config.InputConfig attribute) (nannyml.runner.RunInput attribute) ap_sampling_error() (in module nannyml.sampling_error.binary_classification) ap_sampling_error_components() (in module nannyml.sampling_error.binary_classification) auroc_sampling_error() (in module nannyml.sampling_error.binary_classification) (in module nannyml.sampling_error.multiclass_classification) auroc_sampling_error_components() (in module nannyml.sampling_error.binary_classification) (in module nannyml.sampling_error.multiclass_classification) average_precision_sampling_error() (in module nannyml.sampling_error.multiclass_classification) average_precision_sampling_error_components() (in module nannyml.sampling_error.multiclass_classification)

B

BinaryClassificationAccuracy (class in nannyml.performance_calculation.metrics.binary_classification) (class in nannyml.performance_estimation.confidence_based.metrics) BinaryClassificationAP (class in nannyml.performance_calculation.metrics.binary_classification) (class in nannyml.performance_estimation.confidence_based.metrics) BinaryClassificationAUROC (class in nannyml.performance_calculation.metrics.binary_classification) (class in nannyml.performance_estimation.confidence_based.metrics) BinaryClassificationBusinessValue (class in nannyml.performance_calculation.metrics.binary_classification) (class in nannyml.performance_estimation.confidence_based.metrics) BinaryClassificationConfusionMatrix (class in nannyml.performance_calculation.metrics.binary_classification) (class in nannyml.performance_estimation.confidence_based.metrics) BinaryClassificationF1 (class in nannyml.performance_calculation.metrics.binary_classification) (class in nannyml.performance_estimation.confidence_based.metrics)

BinaryClassificationPrecision (class in nannyml.performance_calculation.metrics.binary_classification) (class in nannyml.performance_estimation.confidence_based.metrics) BinaryClassificationRecall (class in nannyml.performance_calculation.metrics.binary_classification) (class in nannyml.performance_estimation.confidence_based.metrics) BinaryClassificationSpecificity (class in nannyml.performance_calculation.metrics.binary_classification) (class in nannyml.performance_estimation.confidence_based.metrics) BLUE_SKY_CRAYOLA (nannyml.plots.colors.Colors attribute) Business Value Matrix business_value_sampling_error() (in module nannyml.sampling_error.binary_classification) (in module nannyml.sampling_error.multiclass_classification) business_value_sampling_error_components() (in module nannyml.sampling_error.binary_classification) (in module nannyml.sampling_error.multiclass_classification) Butterfly dataset

C

calculate() (nannyml.base.AbstractCalculator method) (nannyml.drift.univariate.methods.Method method) (nannyml.performance_calculation.metrics.base.Metric method) calculate_chunk_distributions() (in module nannyml.distribution.continuous.calculator) (in module nannyml.plots.components.joy_plot) calculate_threshold_values() (in module nannyml.thresholds) calculate_value_counts() (in module nannyml.distribution.categorical.calculator) (in module nannyml.plots.components.stacked_bar_plot) CalculatorConfig (class in nannyml.config) CalculatorException CalculatorFactory (class in nannyml.runner) CalculatorNotFittedException calculators (nannyml.config.Config attribute) calibrate() (nannyml.calibration.Calibrator method) (nannyml.calibration.IsotonicCalibrator method) (nannyml.calibration.NoopCalibrator method) Calibrator (class in nannyml.calibration) CalibratorFactory (class in nannyml.calibration) CATEGORICAL (nannyml.drift.univariate.methods.FeatureType attribute) CategoricalDistributionCalculator (class in nannyml.distribution.categorical.calculator) CategoricalHellingerDistance (class in nannyml.drift.univariate.methods) CategoricalJensenShannonDistance (class in nannyml.drift.univariate.methods) CBPE (class in nannyml.performance_estimation.confidence_based.cbpe) (Confidence-Based Performance Estimation) CBPE_ESTIMATOR_FIT (nannyml.analytics.UsageEvent attribute) (nannyml.usage_logging.UsageEvent attribute) CBPE_ESTIMATOR_RUN (nannyml.analytics.UsageEvent attribute) (nannyml.usage_logging.UsageEvent attribute) CBPE_PLOT (nannyml.usage_logging.UsageEvent attribute) check_and_convert() (in module nannyml.plots.util) check_is_compatible_with() (nannyml.distribution.categorical.result.Result method) (nannyml.distribution.continuous.result.Result method) Chi Squared test Chi2Statistic (class in nannyml.drift.univariate.methods) Child model Chunk (class in nannyml.chunk) chunk_end_dates (nannyml.base.Abstract1DResult property) (nannyml.base.Abstract2DResult property) (nannyml.distribution.categorical.result.Result property) chunk_end_indices (nannyml.base.Abstract1DResult property) (nannyml.base.Abstract2DResult property) (nannyml.distribution.categorical.result.Result property) chunk_indices (nannyml.base.Abstract1DResult property) (nannyml.base.Abstract2DResult property) (nannyml.distribution.categorical.result.Result property) chunk_keys (nannyml.base.Abstract1DResult property) (nannyml.base.Abstract2DResult property) (nannyml.distribution.categorical.result.Result property) chunk_periods (nannyml.base.Abstract1DResult property) (nannyml.base.Abstract2DResult property) (nannyml.distribution.categorical.result.Result property)

chunk_start_dates (nannyml.base.Abstract1DResult property) (nannyml.base.Abstract2DResult property) (nannyml.distribution.categorical.result.Result property) chunk_start_index (nannyml.base.Abstract1DResult property) (nannyml.base.Abstract2DResult property) chunk_start_indices (nannyml.base.Abstract1DResult property) (nannyml.base.Abstract2DResult property) (nannyml.distribution.categorical.result.Result property) Chunker (class in nannyml.chunk) ChunkerException ChunkerFactory (class in nannyml.chunk) CLI_RUN (nannyml.usage_logging.UsageEvent attribute) Colors (class in nannyml.plots.colors) column_name (nannyml.drift.multivariate.data_reconstruction.result.Metric attribute) (nannyml.drift.multivariate.domain_classifier.result.Metric attribute) (nannyml.performance_calculation.metrics.base.Metric property) (nannyml.performance_estimation.confidence_based.metrics.Metric property) column_names (nannyml.performance_calculation.metrics.base.Metric property) (nannyml.performance_estimation.confidence_based.metrics.Metric property) common_nan_removal() (in module nannyml.base) compare() (nannyml.plots.blueprints.comparisons.ResultCompareMixin method) Concept Drift Confidence Band Confidence Score Config (class in nannyml.config) Confusion Matrix ConstantThreshold (class in nannyml.thresholds) CONTINUOUS (nannyml.drift.univariate.methods.FeatureType attribute) ContinuousDistributionCalculator (class in nannyml.distribution.continuous.calculator) ContinuousHellingerDistance (class in nannyml.drift.univariate.methods) ContinuousJensenShannonDistance (class in nannyml.drift.univariate.methods) CorrelationRanker (class in nannyml.drift.ranker) CountBasedChunker (class in nannyml.chunk) Covariate Shift create() (nannyml.calibration.CalibratorFactory class method) (nannyml.drift.univariate.methods.MethodFactory class method) (nannyml.io.base.WriterFactory class method) (nannyml.performance_calculation.metrics.base.MetricFactory class method) (nannyml.performance_estimation.confidence_based.metrics.MetricFactory class method) (nannyml.performance_estimation.direct_loss_estimation.metrics.MetricFactory class method) credentials (nannyml.config.InputDataConfig attribute) (nannyml.config.StoreConfig attribute) cron (nannyml.config.SchedulingConfig attribute) CronSchedulingConfig (class in nannyml.config) crontab (nannyml.config.CronSchedulingConfig attribute) current_calculator (nannyml.runner.RunContext attribute) current_calculator_config (nannyml.runner.RunContext attribute) current_calculator_success (nannyml.runner.RunContext attribute) current_step (nannyml.runner.RunContext attribute)

D

d() (in module nannyml.data_quality.unseen) Data Chunk Data Drift Data Period DataReconstructionDriftCalculator (class in nannyml.drift.multivariate.data_reconstruction.calculator) days (nannyml.config.IntervalSchedulingConfig attribute) DC_CALC_FIT (nannyml.usage_logging.UsageEvent attribute) DC_CALC_RUN (nannyml.usage_logging.UsageEvent attribute) DC_RESULTS_PLOT (nannyml.usage_logging.UsageEvent attribute) DEFAULT_CHUNK_COUNT (nannyml.chunk.DefaultChunker attribute) DEFAULT_COLUMNS (nannyml.base.AbstractEstimatorResult attribute) (nannyml.base.AbstractResult attribute) DefaultChunker (class in nannyml.chunk) deserialize() (nannyml.io.store.serializers.Serializer method) DeserializeException disable_usage_logging() (in module nannyml.usage_logging) display_name (nannyml.drift.multivariate.data_reconstruction.result.Metric attribute) (nannyml.drift.multivariate.domain_classifier.result.Metric attribute) (nannyml.performance_calculation.metrics.base.Metric property) (nannyml.performance_estimation.confidence_based.metrics.Metric property)

display_names (nannyml.performance_calculation.metrics.base.Metric property) (nannyml.performance_estimation.confidence_based.metrics.Metric property) DLE (class in nannyml.performance_estimation.direct_loss_estimation.dle) DLE_ESTIMATOR_FIT (nannyml.usage_logging.UsageEvent attribute) DLE_ESTIMATOR_RUN (nannyml.usage_logging.UsageEvent attribute) DLE_PLOT (nannyml.usage_logging.UsageEvent attribute) Domain Classifier DomainClassifierCalculator (class in nannyml.drift.multivariate.domain_classifier.calculator) DQ_CALC_MISSING_VALUES_FIT (nannyml.usage_logging.UsageEvent attribute) DQ_CALC_MISSING_VALUES_PLOT (nannyml.usage_logging.UsageEvent attribute) DQ_CALC_MISSING_VALUES_RUN (nannyml.usage_logging.UsageEvent attribute) DQ_CALC_UNSEEN_VALUES_FIT (nannyml.usage_logging.UsageEvent attribute) DQ_CALC_UNSEEN_VALUES_PLOT (nannyml.usage_logging.UsageEvent attribute) DQ_CALC_UNSEEN_VALUES_RUN (nannyml.usage_logging.UsageEvent attribute) DQ_CALC_VALUES_OUT_OF_RANGE_FIT (nannyml.usage_logging.UsageEvent attribute) DQ_CALC_VALUES_OUT_OF_RANGE_PLOT (nannyml.usage_logging.UsageEvent attribute) DQ_CALC_VALUES_OUT_OF_RANGE_RUN (nannyml.usage_logging.UsageEvent attribute)

E

empty (nannyml.base.AbstractEstimatorResult property) (nannyml.base.AbstractResult property) enable_usage_logging() (in module nannyml.usage_logging) enabled (nannyml.config.CalculatorConfig attribute) ensure_numpy() (in module nannyml.plots.util) Error estimate() (nannyml.base.AbstractEstimator method) (nannyml.performance_estimation.direct_loss_estimation.metrics.Metric method) estimate_accuracy() (in module nannyml.performance_estimation.confidence_based.metrics)

estimate_ap() (in module nannyml.performance_estimation.confidence_based.metrics) estimate_business_value() (in module nannyml.performance_estimation.confidence_based.metrics) estimate_f1() (in module nannyml.performance_estimation.confidence_based.metrics) estimate_precision() (in module nannyml.performance_estimation.confidence_based.metrics) estimate_recall() (in module nannyml.performance_estimation.confidence_based.metrics) estimate_roc_auc() (in module nannyml.performance_estimation.confidence_based.metrics) estimate_specificity() (in module nannyml.performance_estimation.confidence_based.metrics) Estimated Performance EstimatorException

F

f1_sampling_error() (in module nannyml.sampling_error.binary_classification) (in module nannyml.sampling_error.multiclass_classification) f1_sampling_error_components() (in module nannyml.sampling_error.binary_classification) (in module nannyml.sampling_error.multiclass_classification) false_negative_sampling_error() (in module nannyml.sampling_error.binary_classification) false_negative_sampling_error_components() (in module nannyml.sampling_error.binary_classification) false_positive_sampling_error() (in module nannyml.sampling_error.binary_classification) false_positive_sampling_error_components() (in module nannyml.sampling_error.binary_classification) Feature FeatureType (class in nannyml.drift.univariate.methods) Figure (class in nannyml.plots.components.figure) filename (nannyml.config.StoreConfig attribute) FileReader (class in nannyml.io.file_reader) FilesystemStore (class in nannyml.io.store.file_store) FileWriter (class in nannyml.io.file_writer) filter() (nannyml.base.AbstractEstimatorResult method) (nannyml.base.AbstractResult method)

fit() (nannyml.base.AbstractCalculator method) (nannyml.base.AbstractEstimator method) (nannyml.calibration.Calibrator method) (nannyml.calibration.IsotonicCalibrator method) (nannyml.calibration.NoopCalibrator method) (nannyml.drift.ranker.CorrelationRanker method) (nannyml.drift.univariate.methods.Chi2Statistic method) (nannyml.drift.univariate.methods.Method method) (nannyml.performance_calculation.metrics.base.Metric method) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationConfusionMatrix method) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationConfusionMatrix method) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationConfusionMatrix method) (nannyml.performance_estimation.confidence_based.metrics.Metric method) (nannyml.performance_estimation.confidence_based.metrics.MulticlassClassificationConfusionMatrix method) (nannyml.performance_estimation.direct_loss_estimation.metrics.Metric method)

G

get_chunk_record() (nannyml.performance_calculation.metrics.base.Metric method) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationConfusionMatrix method) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationConfusionMatrix method) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationConfusionMatrix method) (nannyml.performance_estimation.confidence_based.metrics.Metric method) (nannyml.performance_estimation.confidence_based.metrics.MulticlassClassificationConfusionMatrix method) get_chunker() (nannyml.chunk.ChunkerFactory class method) get_config_path() (in module nannyml.config) get_custom_data() (nannyml.plots.components.hover.Hover method) get_false_neg_info() (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationConfusionMatrix method) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationConfusionMatrix method) get_false_negative_estimate() (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationConfusionMatrix method) get_false_pos_info() (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationConfusionMatrix method) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationConfusionMatrix method) get_false_positive_estimate() (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationConfusionMatrix method)

get_filepath_str() (in module nannyml.io.base) get_logger() (in module nannyml.usage_logging) get_output_writers() (in module nannyml.runner) get_store() (in module nannyml.runner) get_template() (nannyml.plots.components.hover.Hover method) get_title() (nannyml.plots.blueprints.comparisons.ResultCompareMixin method) get_true_neg_info() (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationConfusionMatrix method) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationConfusionMatrix method) get_true_negative_estimate() (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationConfusionMatrix method) get_true_pos_info() (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationConfusionMatrix method) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationConfusionMatrix method) get_true_positive_estimate() (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationConfusionMatrix method) GRAY (nannyml.plots.colors.Colors attribute) GRAY_DARK (nannyml.plots.colors.Colors attribute) GREEN_SEA (nannyml.plots.colors.Colors attribute) Ground truth

H

has_non_null_data() (in module nannyml.plots.util)

hours (nannyml.config.IntervalSchedulingConfig attribute) Hover (class in nannyml.plots.components.hover)

I

Identifier ignore_errors (nannyml.config.Config attribute) Imputation increase_step() (nannyml.runner.RunContext method) INDIGO_PERSIAN (nannyml.plots.colors.Colors attribute) input (nannyml.config.Config attribute) InputConfig (class in nannyml.config) InputDataConfig (class in nannyml.config)

interval (nannyml.config.SchedulingConfig attribute) IntervalSchedulingConfig (class in nannyml.config) InvalidArgumentsException invalidate (nannyml.config.StoreConfig attribute) InvalidReferenceDataException IOException is_time_based_x_axis() (in module nannyml.plots.util) IsotonicCalibrator (class in nannyml.calibration)

J

JoblibPickleSerializer (class in nannyml.io.store.serializers)

join_column (nannyml.config.TargetDataConfig attribute) joy() (in module nannyml.plots.components.joy_plot)

K

keys() (nannyml.base.AbstractResult method) (nannyml.data_quality.missing.result.Result method) (nannyml.data_quality.range.result.Result method) (nannyml.data_quality.unseen.result.Result method) (nannyml.distribution.categorical.result.Result method) (nannyml.distribution.continuous.result.Result method) (nannyml.drift.multivariate.data_reconstruction.result.Result method) (nannyml.drift.multivariate.domain_classifier.result.Result method) (nannyml.drift.univariate.result.Result method) (nannyml.performance_calculation.result.Result method) (nannyml.performance_estimation.confidence_based.results.Result method) (nannyml.performance_estimation.direct_loss_estimation.result.Result method) (nannyml.stats.avg.result.Result method) (nannyml.stats.count.result.Result method) (nannyml.stats.median.result.Result method) (nannyml.stats.std.result.Result method) (nannyml.stats.sum.result.Result method)

Kolmogorov-Smirnov test KolmogorovSmirnovStatistic (class in nannyml.drift.univariate.methods)

L

Label Latent space LIGHT_GRAY (nannyml.plots.colors.Colors attribute) LInfinityDistance (class in nannyml.drift.univariate.methods) load() (nannyml.config.Config class method) (nannyml.io.store.base.Store method) load_csv_file_to_df() (in module nannyml.datasets.datasets) load_modified_california_housing_dataset() (in module nannyml.datasets.datasets) load_pq_file_to_df() (in module nannyml.datasets.datasets) load_synthetic_binary_classification_dataset() (in module nannyml.datasets.datasets) load_synthetic_car_loan_data_quality_dataset() (in module nannyml.datasets.datasets) load_synthetic_car_loan_dataset() (in module nannyml.datasets.datasets)

load_synthetic_car_price_dataset() (in module nannyml.datasets.datasets) load_synthetic_multiclass_classification_dataset() (in module nannyml.datasets.datasets) load_titanic_dataset() (in module nannyml.datasets.datasets) load_us_census_ma_employment_data() (in module nannyml.datasets.datasets) log() (nannyml.runner.RunnerLogger method) (nannyml.usage_logging.UsageLogger method) log_usage() (in module nannyml.usage_logging) Loss Loss Function lower (nannyml.thresholds.ConstantThreshold attribute) lower_confidence_bounds() (nannyml.base.AbstractResult method) lower_thresholds() (nannyml.base.AbstractResult method)

M

MAE (class in nannyml.performance_calculation.metrics.regression) (class in nannyml.performance_estimation.direct_loss_estimation.metrics) mae_sampling_error() (in module nannyml.sampling_error.regression) mae_sampling_error_components() (in module nannyml.sampling_error.regression) MAPE (class in nannyml.performance_calculation.metrics.regression) (class in nannyml.performance_estimation.direct_loss_estimation.metrics) mape_sampling_error() (in module nannyml.sampling_error.regression) mape_sampling_error_components() (in module nannyml.sampling_error.regression) merge() (nannyml.chunk.Chunk method) Method (class in nannyml.drift.univariate.methods) MethodFactory (class in nannyml.drift.univariate.methods) methods (nannyml.drift.univariate.result.Result property) Metric (class in nannyml.drift.multivariate.data_reconstruction.result) (class in nannyml.drift.multivariate.domain_classifier.result) (class in nannyml.performance_calculation.metrics.base) (class in nannyml.performance_estimation.confidence_based.metrics) (class in nannyml.performance_estimation.direct_loss_estimation.metrics) metric() (in module nannyml.plots.components.step_plot) MetricFactory (class in nannyml.performance_calculation.metrics.base) (class in nannyml.performance_estimation.confidence_based.metrics) (class in nannyml.performance_estimation.direct_loss_estimation.metrics) metrics (nannyml.performance_calculation.result.Result attribute) minutes (nannyml.config.IntervalSchedulingConfig attribute) MissingMetadataException MissingValuesCalculator (class in nannyml.data_quality.missing.calculator) Model inputs Model outputs Model predictions model_computed_fields (nannyml.config.CalculatorConfig attribute) (nannyml.config.Config attribute) (nannyml.config.CronSchedulingConfig attribute) (nannyml.config.InputConfig attribute) (nannyml.config.InputDataConfig attribute) (nannyml.config.IntervalSchedulingConfig attribute) (nannyml.config.SchedulingConfig attribute) (nannyml.config.StoreConfig attribute) (nannyml.config.TargetDataConfig attribute) (nannyml.config.WriterConfig attribute) model_config (nannyml.config.CalculatorConfig attribute) (nannyml.config.Config attribute) (nannyml.config.CronSchedulingConfig attribute) (nannyml.config.InputConfig attribute) (nannyml.config.InputDataConfig attribute) (nannyml.config.IntervalSchedulingConfig attribute) (nannyml.config.SchedulingConfig attribute) (nannyml.config.StoreConfig attribute) (nannyml.config.TargetDataConfig attribute) (nannyml.config.WriterConfig attribute) model_fields (nannyml.config.CalculatorConfig attribute) (nannyml.config.Config attribute) (nannyml.config.CronSchedulingConfig attribute) (nannyml.config.InputConfig attribute) (nannyml.config.InputDataConfig attribute) (nannyml.config.IntervalSchedulingConfig attribute) (nannyml.config.SchedulingConfig attribute) (nannyml.config.StoreConfig attribute) (nannyml.config.TargetDataConfig attribute) (nannyml.config.WriterConfig attribute) module nannyml nannyml.analytics nannyml.base nannyml.calibration nannyml.chunk nannyml.cli nannyml.cli.cli nannyml.cli.run nannyml.config nannyml.data_quality nannyml.data_quality.missing nannyml.data_quality.missing.calculator nannyml.data_quality.missing.result nannyml.data_quality.range nannyml.data_quality.range.calculator nannyml.data_quality.range.result nannyml.data_quality.unseen nannyml.data_quality.unseen.calculator nannyml.data_quality.unseen.result nannyml.datasets nannyml.datasets.data nannyml.datasets.datasets nannyml.distribution nannyml.distribution.categorical nannyml.distribution.categorical.calculator nannyml.distribution.categorical.result nannyml.distribution.continuous nannyml.distribution.continuous.calculator nannyml.distribution.continuous.result nannyml.drift nannyml.drift.multivariate nannyml.drift.multivariate.data_reconstruction nannyml.drift.multivariate.data_reconstruction.calculator nannyml.drift.multivariate.data_reconstruction.result nannyml.drift.multivariate.domain_classifier nannyml.drift.multivariate.domain_classifier.calculator nannyml.drift.multivariate.domain_classifier.result nannyml.drift.ranker nannyml.drift.univariate nannyml.drift.univariate.calculator nannyml.drift.univariate.methods nannyml.drift.univariate.result nannyml.exceptions nannyml.io nannyml.io.base nannyml.io.file_reader nannyml.io.file_writer nannyml.io.pickle_file_writer nannyml.io.raw_files_writer nannyml.io.store nannyml.io.store.base nannyml.io.store.file_store nannyml.io.store.serializers nannyml.performance_calculation nannyml.performance_calculation.calculator nannyml.performance_calculation.metrics nannyml.performance_calculation.metrics.base nannyml.performance_calculation.metrics.binary_classification nannyml.performance_calculation.metrics.multiclass_classification nannyml.performance_calculation.metrics.regression nannyml.performance_calculation.result nannyml.performance_estimation nannyml.performance_estimation.confidence_based nannyml.performance_estimation.confidence_based.cbpe nannyml.performance_estimation.confidence_based.metrics nannyml.performance_estimation.confidence_based.results nannyml.performance_estimation.direct_loss_estimation nannyml.performance_estimation.direct_loss_estimation.dle nannyml.performance_estimation.direct_loss_estimation.metrics nannyml.performance_estimation.direct_loss_estimation.result nannyml.plots nannyml.plots.blueprints nannyml.plots.blueprints.comparisons nannyml.plots.blueprints.distributions nannyml.plots.blueprints.metrics nannyml.plots.colors nannyml.plots.components nannyml.plots.components.figure nannyml.plots.components.hover nannyml.plots.components.joy_plot nannyml.plots.components.stacked_bar_plot nannyml.plots.components.step_plot nannyml.plots.util nannyml.runner nannyml.sampling_error nannyml.sampling_error.binary_classification nannyml.sampling_error.multiclass_classification nannyml.sampling_error.regression nannyml.sampling_error.summary_stats nannyml.stats nannyml.stats.avg nannyml.stats.avg.calculator nannyml.stats.avg.result nannyml.stats.count nannyml.stats.count.calculator nannyml.stats.count.result nannyml.stats.median nannyml.stats.median.calculator nannyml.stats.median.result nannyml.stats.std nannyml.stats.std.calculator nannyml.stats.std.result nannyml.stats.sum nannyml.stats.sum.calculator nannyml.stats.sum.result nannyml.thresholds nannyml.usage_logging

MSE (class in nannyml.performance_calculation.metrics.regression) (class in nannyml.performance_estimation.direct_loss_estimation.metrics) mse_sampling_error() (in module nannyml.sampling_error.regression) mse_sampling_error_components() (in module nannyml.sampling_error.regression) MSLE (class in nannyml.performance_calculation.metrics.regression) (class in nannyml.performance_estimation.direct_loss_estimation.metrics) msle_sampling_error() (in module nannyml.sampling_error.regression) msle_sampling_error_components() (in module nannyml.sampling_error.regression) multiclass_confusion_matrix_sampling_error() (in module nannyml.sampling_error.multiclass_classification) multiclass_confusion_matrix_sampling_error_components() (in module nannyml.sampling_error.multiclass_classification) MulticlassClassificationAccuracy (class in nannyml.performance_calculation.metrics.multiclass_classification) (class in nannyml.performance_estimation.confidence_based.metrics) MulticlassClassificationAP (class in nannyml.performance_calculation.metrics.multiclass_classification) (class in nannyml.performance_estimation.confidence_based.metrics) MulticlassClassificationAUROC (class in nannyml.performance_calculation.metrics.multiclass_classification) (class in nannyml.performance_estimation.confidence_based.metrics) MulticlassClassificationBusinessValue (class in nannyml.performance_calculation.metrics.multiclass_classification) (class in nannyml.performance_estimation.confidence_based.metrics) MulticlassClassificationConfusionMatrix (class in nannyml.performance_calculation.metrics.multiclass_classification) (class in nannyml.performance_estimation.confidence_based.metrics) MulticlassClassificationF1 (class in nannyml.performance_calculation.metrics.multiclass_classification) (class in nannyml.performance_estimation.confidence_based.metrics) MulticlassClassificationPrecision (class in nannyml.performance_calculation.metrics.multiclass_classification) (class in nannyml.performance_estimation.confidence_based.metrics) MulticlassClassificationRecall (class in nannyml.performance_calculation.metrics.multiclass_classification) (class in nannyml.performance_estimation.confidence_based.metrics) MulticlassClassificationSpecificity (class in nannyml.performance_calculation.metrics.multiclass_classification) (class in nannyml.performance_estimation.confidence_based.metrics) MULTIVAR_DRIFT_CALC_FIT (nannyml.usage_logging.UsageEvent attribute) MULTIVAR_DRIFT_CALC_RUN (nannyml.usage_logging.UsageEvent attribute) MULTIVAR_DRIFT_PLOT (nannyml.usage_logging.UsageEvent attribute) MULTIVAR_RECONST_DRIFT_CALC_FIT (nannyml.analytics.UsageEvent attribute) MULTIVAR_RECONST_DRIFT_CALC_RUN (nannyml.analytics.UsageEvent attribute) Multivariate Drift Detection

N

name (nannyml.config.CalculatorConfig attribute) Nanny model nannyml module nannyml.analytics module nannyml.base module nannyml.calibration module nannyml.chunk module nannyml.cli module nannyml.cli.cli module nannyml.cli.run module nannyml.config module nannyml.data_quality module nannyml.data_quality.missing module nannyml.data_quality.missing.calculator module nannyml.data_quality.missing.result module nannyml.data_quality.range module nannyml.data_quality.range.calculator module nannyml.data_quality.range.result module nannyml.data_quality.unseen module nannyml.data_quality.unseen.calculator module nannyml.data_quality.unseen.result module nannyml.datasets module nannyml.datasets.data module nannyml.datasets.datasets module nannyml.distribution module nannyml.distribution.categorical module nannyml.distribution.categorical.calculator module nannyml.distribution.categorical.result module nannyml.distribution.continuous module nannyml.distribution.continuous.calculator module nannyml.distribution.continuous.result module nannyml.drift module nannyml.drift.multivariate module nannyml.drift.multivariate.data_reconstruction module nannyml.drift.multivariate.data_reconstruction.calculator module nannyml.drift.multivariate.data_reconstruction.result module nannyml.drift.multivariate.domain_classifier module nannyml.drift.multivariate.domain_classifier.calculator module nannyml.drift.multivariate.domain_classifier.result module nannyml.drift.ranker module nannyml.drift.univariate module nannyml.drift.univariate.calculator module nannyml.drift.univariate.methods module nannyml.drift.univariate.result module nannyml.exceptions module nannyml.io module nannyml.io.base module nannyml.io.file_reader module nannyml.io.file_writer module nannyml.io.pickle_file_writer module nannyml.io.raw_files_writer module nannyml.io.store module nannyml.io.store.base module nannyml.io.store.file_store module nannyml.io.store.serializers module nannyml.performance_calculation module

nannyml.performance_calculation.calculator module nannyml.performance_calculation.metrics module nannyml.performance_calculation.metrics.base module nannyml.performance_calculation.metrics.binary_classification module nannyml.performance_calculation.metrics.multiclass_classification module nannyml.performance_calculation.metrics.regression module nannyml.performance_calculation.result module nannyml.performance_estimation module nannyml.performance_estimation.confidence_based module nannyml.performance_estimation.confidence_based.cbpe module nannyml.performance_estimation.confidence_based.metrics module nannyml.performance_estimation.confidence_based.results module nannyml.performance_estimation.direct_loss_estimation module nannyml.performance_estimation.direct_loss_estimation.dle module nannyml.performance_estimation.direct_loss_estimation.metrics module nannyml.performance_estimation.direct_loss_estimation.result module nannyml.plots module nannyml.plots.blueprints module nannyml.plots.blueprints.comparisons module nannyml.plots.blueprints.distributions module nannyml.plots.blueprints.metrics module nannyml.plots.colors module nannyml.plots.components module nannyml.plots.components.figure module nannyml.plots.components.hover module nannyml.plots.components.joy_plot module nannyml.plots.components.stacked_bar_plot module nannyml.plots.components.step_plot module nannyml.plots.util module nannyml.runner module nannyml.sampling_error module nannyml.sampling_error.binary_classification module nannyml.sampling_error.multiclass_classification module nannyml.sampling_error.regression module nannyml.sampling_error.summary_stats module nannyml.stats module nannyml.stats.avg module nannyml.stats.avg.calculator module nannyml.stats.avg.result module nannyml.stats.count module nannyml.stats.count.calculator module nannyml.stats.count.result module nannyml.stats.median module nannyml.stats.median.calculator module nannyml.stats.median.result module nannyml.stats.std module nannyml.stats.std.calculator module nannyml.stats.std.result module nannyml.stats.sum module nannyml.stats.sum.calculator module nannyml.stats.sum.result module nannyml.thresholds module nannyml.usage_logging module NannyMLException needs_calibration() (in module nannyml.calibration) NoopCalibrator (class in nannyml.calibration) NotFittedException NumericalRangeCalculator (class in nannyml.data_quality.range.calculator)

O

OUTPUT_DRIFT_CALC_FIT (nannyml.analytics.UsageEvent attribute)

OUTPUT_DRIFT_CALC_RUN (nannyml.analytics.UsageEvent attribute) outputs (nannyml.config.CalculatorConfig attribute)

P

pairwise() (in module nannyml.plots.util) params (nannyml.config.CalculatorConfig attribute) (nannyml.config.WriterConfig attribute) parse() (nannyml.config.Config class method) parse_object() (nannyml.thresholds.Threshold class method) Partition Column path (nannyml.config.InputDataConfig attribute) (nannyml.config.StoreConfig attribute) PCA PerColumnResult (class in nannyml.base) Performance Estimation PERFORMANCE_CALC_FIT (nannyml.analytics.UsageEvent attribute) (nannyml.usage_logging.UsageEvent attribute) PERFORMANCE_CALC_RUN (nannyml.analytics.UsageEvent attribute) (nannyml.usage_logging.UsageEvent attribute) PERFORMANCE_PLOT (nannyml.usage_logging.UsageEvent attribute) PerformanceCalculator (class in nannyml.performance_calculation.calculator) PeriodBasedChunker (class in nannyml.chunk) PerMetricPerColumnResult (class in nannyml.base) PerMetricResult (class in nannyml.base) PickleFileWriter (class in nannyml.io.pickle_file_writer) PickleSerializer (class in nannyml.io.store.serializers) plot() (nannyml.base.AbstractEstimatorResult method) (nannyml.base.AbstractResult method) (nannyml.data_quality.missing.result.Result method) (nannyml.data_quality.range.result.Result method) (nannyml.data_quality.unseen.result.Result method) (nannyml.distribution.categorical.result.Result method) (nannyml.distribution.continuous.result.Result method) (nannyml.drift.multivariate.data_reconstruction.result.Result method) (nannyml.drift.multivariate.domain_classifier.result.Result method) (nannyml.drift.univariate.result.Result method) (nannyml.performance_calculation.result.Result method) (nannyml.performance_estimation.confidence_based.results.Result method) (nannyml.performance_estimation.direct_loss_estimation.result.Result method) (nannyml.plots.blueprints.comparisons.ResultComparison method) (nannyml.stats.avg.result.Result method) (nannyml.stats.count.result.Result method) (nannyml.stats.median.result.Result method) (nannyml.stats.std.result.Result method) (nannyml.stats.sum.result.Result method)

plot_2d_compare_step_to_step() (in module nannyml.plots.blueprints.comparisons) plot_distributions() (in module nannyml.plots.blueprints.distributions) plot_metric() (in module nannyml.plots.blueprints.metrics) plot_metrics() (in module nannyml.plots.blueprints.metrics) precision_sampling_error() (in module nannyml.sampling_error.binary_classification) (in module nannyml.sampling_error.multiclass_classification) precision_sampling_error_components() (in module nannyml.sampling_error.binary_classification) (in module nannyml.sampling_error.multiclass_classification) Predicted labels Predicted probabilities Predicted scores Predictions preprocess_categorical_features() (in module nannyml.drift.multivariate.domain_classifier.calculator)

R

raise_if_metrics_require_y_pred() (in module nannyml.performance_calculation.calculator) (in module nannyml.performance_estimation.confidence_based.cbpe) rank() (nannyml.drift.ranker.AlertCountRanker method) (nannyml.drift.ranker.CorrelationRanker method) RANKER_ALERT_COUNT_RUN (nannyml.usage_logging.UsageEvent attribute) RANKER_CORRELATION_FIT (nannyml.usage_logging.UsageEvent attribute) RANKER_CORRELATION_RUN (nannyml.usage_logging.UsageEvent attribute) Ranking RawFilesWriter (class in nannyml.io.raw_files_writer) read() (nannyml.io.base.Reader method) read_args (nannyml.config.InputDataConfig attribute) read_data() (in module nannyml.runner) Reader (class in nannyml.io.base) ReaderException Realized Performance realized_performance() (nannyml.performance_estimation.direct_loss_estimation.metrics.MAE method) (nannyml.performance_estimation.direct_loss_estimation.metrics.MAPE method) (nannyml.performance_estimation.direct_loss_estimation.metrics.Metric method) (nannyml.performance_estimation.direct_loss_estimation.metrics.MSE method) (nannyml.performance_estimation.direct_loss_estimation.metrics.MSLE method) (nannyml.performance_estimation.direct_loss_estimation.metrics.RMSE method) (nannyml.performance_estimation.direct_loss_estimation.metrics.RMSLE method) recall_sampling_error() (in module nannyml.sampling_error.binary_classification) (in module nannyml.sampling_error.multiclass_classification) recall_sampling_error_components() (in module nannyml.sampling_error.binary_classification) (in module nannyml.sampling_error.multiclass_classification) Reconstruction Error RED_IMPERIAL (nannyml.plots.colors.Colors attribute) reference_data (nannyml.config.InputConfig attribute) (nannyml.runner.RunInput attribute) register() (nannyml.calibration.CalibratorFactory class method) (nannyml.drift.univariate.methods.MethodFactory class method) (nannyml.io.base.WriterFactory class method) (nannyml.performance_calculation.metrics.base.MetricFactory class method) (nannyml.performance_estimation.confidence_based.metrics.MetricFactory class method) (nannyml.performance_estimation.direct_loss_estimation.metrics.MetricFactory class method) (nannyml.runner.CalculatorFactory class method) register_calibrator() (nannyml.calibration.CalibratorFactory class method) registry (nannyml.drift.univariate.methods.MethodFactory attribute) (nannyml.io.base.WriterFactory attribute) (nannyml.performance_calculation.metrics.base.MetricFactory attribute) (nannyml.performance_estimation.confidence_based.metrics.MetricFactory attribute) (nannyml.performance_estimation.direct_loss_estimation.metrics.MetricFactory attribute) (nannyml.runner.CalculatorFactory attribute)

render_alert_string() (in module nannyml.plots.components.hover) render_display_name() (in module nannyml.plots.blueprints.comparisons) render_metric_display_name() (in module nannyml.plots.blueprints.comparisons) render_partial_target_string() (in module nannyml.plots.components.hover) render_period_string() (in module nannyml.plots.components.hover) render_x_coordinate() (in module nannyml.plots.components.hover) Residual Result (class in nannyml.data_quality.missing.result) (class in nannyml.data_quality.range.result) (class in nannyml.data_quality.unseen.result) (class in nannyml.distribution.categorical.result) (class in nannyml.distribution.continuous.result) (class in nannyml.drift.multivariate.data_reconstruction.result) (class in nannyml.drift.multivariate.domain_classifier.result) (class in nannyml.drift.univariate.result) (class in nannyml.performance_calculation.result) (class in nannyml.performance_estimation.confidence_based.results) (class in nannyml.performance_estimation.direct_loss_estimation.result) (class in nannyml.stats.avg.result) (class in nannyml.stats.count.result) (class in nannyml.stats.median.result) (class in nannyml.stats.std.result) (class in nannyml.stats.sum.result) result (nannyml.runner.RunContext attribute) ResultCompareMixin (class in nannyml.plots.blueprints.comparisons) ResultComparison (class in nannyml.plots.blueprints.comparisons) RMSE (class in nannyml.performance_calculation.metrics.regression) (class in nannyml.performance_estimation.direct_loss_estimation.metrics) rmse_sampling_error() (in module nannyml.sampling_error.regression) rmse_sampling_error_components() (in module nannyml.sampling_error.regression) RMSLE (class in nannyml.performance_calculation.metrics.regression) (class in nannyml.performance_estimation.direct_loss_estimation.metrics) rmsle_sampling_error() (in module nannyml.sampling_error.regression) rmsle_sampling_error_components() (in module nannyml.sampling_error.regression) run() (in module nannyml.runner) run_context() (in module nannyml.runner) run_success (nannyml.runner.RunContext attribute) RunContext (class in nannyml.runner) RunInput (class in nannyml.runner) RunnerLogger (class in nannyml.runner)

S

SAFFRON (nannyml.plots.colors.Colors attribute) Sampling Error sampling_error() (nannyml.base.AbstractResult method) (nannyml.performance_calculation.metrics.base.Metric method) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationConfusionMatrix method) (nannyml.performance_estimation.direct_loss_estimation.metrics.Metric method) scheduling (nannyml.config.Config attribute) SchedulingConfig (class in nannyml.config) SEGMENT_WRITE_KEY (nannyml.analytics.SegmentUsageTracker attribute) (nannyml.usage_logging.SegmentUsageTracker attribute) SegmentUsageTracker (class in nannyml.analytics) (class in nannyml.usage_logging) serialize() (nannyml.io.store.serializers.Serializer method) SerializeException Serializer (class in nannyml.io.store.serializers) SizeBasedChunker (class in nannyml.chunk) specificity_sampling_error() (in module nannyml.sampling_error.binary_classification) (in module nannyml.sampling_error.multiclass_classification) specificity_sampling_error_components() (in module nannyml.sampling_error.binary_classification) (in module nannyml.sampling_error.multiclass_classification) split() (nannyml.chunk.Chunker method) stacked_bar() (in module nannyml.plots.components.stacked_bar_plot) Standard Error StandardDeviationThreshold (class in nannyml.thresholds) STATS_AVG_FIT (nannyml.usage_logging.UsageEvent attribute) STATS_AVG_PLOT (nannyml.usage_logging.UsageEvent attribute) STATS_AVG_RUN (nannyml.usage_logging.UsageEvent attribute) STATS_COUNT_FIT (nannyml.usage_logging.UsageEvent attribute)

STATS_COUNT_PLOT (nannyml.usage_logging.UsageEvent attribute) STATS_COUNT_RUN (nannyml.usage_logging.UsageEvent attribute) STATS_MEDIAN_FIT (nannyml.usage_logging.UsageEvent attribute) STATS_MEDIAN_PLOT (nannyml.usage_logging.UsageEvent attribute) STATS_MEDIAN_RUN (nannyml.usage_logging.UsageEvent attribute) STATS_STD_FIT (nannyml.usage_logging.UsageEvent attribute) STATS_STD_PLOT (nannyml.usage_logging.UsageEvent attribute) STATS_STD_RUN (nannyml.usage_logging.UsageEvent attribute) STATS_SUM_FIT (nannyml.usage_logging.UsageEvent attribute) STATS_SUM_PLOT (nannyml.usage_logging.UsageEvent attribute) STATS_SUM_RUN (nannyml.usage_logging.UsageEvent attribute) std_lower_multiplier (nannyml.thresholds.StandardDeviationThreshold attribute) std_upper_multiplier (nannyml.thresholds.StandardDeviationThreshold attribute) STEPS_PER_CALCULATOR (nannyml.runner.RunContext attribute) Store (class in nannyml.io.store.base) store (nannyml.config.CalculatorConfig attribute) store() (nannyml.io.store.base.Store method) StoreConfig (class in nannyml.config) StoreException summary_stats_median_sampling_error() (in module nannyml.sampling_error.summary_stats) summary_stats_median_sampling_error_components() (in module nannyml.sampling_error.summary_stats) summary_stats_std_sampling_error() (in module nannyml.sampling_error.summary_stats) summary_stats_std_sampling_error_components() (in module nannyml.sampling_error.summary_stats) SummaryStatsAvgCalculator (class in nannyml.stats.avg.calculator) SummaryStatsMedianCalculator (class in nannyml.stats.median.calculator) SummaryStatsRowCountCalculator (class in nannyml.stats.count.calculator) SummaryStatsStdCalculator (class in nannyml.stats.std.calculator) SummaryStatsSumCalculator (class in nannyml.stats.sum.calculator) SUPPORTED_METRIC_STYLES (nannyml.plots.components.figure.Figure attribute)

T

Target target_data (nannyml.config.InputConfig attribute) (nannyml.runner.RunInput attribute) TARGET_DISTRIBUTION_DRIFT_CALC_FIT (nannyml.analytics.UsageEvent attribute) TARGET_DISTRIBUTION_DRIFT_CALC_RUN (nannyml.analytics.UsageEvent attribute) target_join_column (nannyml.runner.RunInput attribute) TargetDataConfig (class in nannyml.config) TEST_UUID (nannyml.analytics.SegmentUsageTracker attribute) Threshold (class in nannyml.thresholds) ThresholdException thresholds() (nannyml.thresholds.ConstantThreshold method) (nannyml.thresholds.StandardDeviationThreshold method) (nannyml.thresholds.Threshold method) Timestamp

titles (nannyml.plots.blueprints.comparisons.ResultCompareMixin property) to_df() (nannyml.base.AbstractEstimatorResult method) (nannyml.base.AbstractResult method) (nannyml.distribution.categorical.result.Result method) total_steps (nannyml.runner.RunContext attribute) track() (in module nannyml.analytics) (nannyml.analytics.UsageTracker method) transparent() (nannyml.plots.colors.Colors method) true_negative_sampling_error() (in module nannyml.sampling_error.binary_classification) true_negative_sampling_error_components() (in module nannyml.sampling_error.binary_classification) true_positive_sampling_error() (in module nannyml.sampling_error.binary_classification) true_positive_sampling_error_components() (in module nannyml.sampling_error.binary_classification) tune_hyperparams() (nannyml.drift.multivariate.domain_classifier.calculator.DomainClassifierCalculator method) type (nannyml.config.CalculatorConfig attribute) (nannyml.config.WriterConfig attribute)

U

UNIVAR_DRIFT_CALC_FIT (nannyml.usage_logging.UsageEvent attribute) UNIVAR_DRIFT_CALC_RUN (nannyml.usage_logging.UsageEvent attribute) UNIVAR_DRIFT_PLOT (nannyml.usage_logging.UsageEvent attribute) UNIVAR_STAT_DRIFT_CALC_FIT (nannyml.analytics.UsageEvent attribute) UNIVAR_STAT_DRIFT_CALC_RUN (nannyml.analytics.UsageEvent attribute) Univariate Drift Detection UnivariateDriftCalculator (class in nannyml.drift.univariate.calculator) Unseen Values

UnseenValuesCalculator (class in nannyml.data_quality.unseen.calculator) upper (nannyml.thresholds.ConstantThreshold attribute) upper_confidence_bounds() (nannyml.base.AbstractResult method) upper_thresholds() (nannyml.base.AbstractResult method) UsageEvent (class in nannyml.analytics) (class in nannyml.usage_logging) UsageLogger (class in nannyml.usage_logging) UsageTracker (class in nannyml.analytics) user_metadata (nannyml.analytics.UsageTracker attribute)

V

value_counts() (nannyml.distribution.categorical.result.Result method)

values() (nannyml.base.AbstractResult method)

W

WassersteinDistance (class in nannyml.drift.univariate.methods) weeks (nannyml.config.IntervalSchedulingConfig attribute) write() (nannyml.io.base.Writer method) write_args (nannyml.config.WriterConfig attribute) WRITE_DB (nannyml.usage_logging.UsageEvent attribute) write_key (nannyml.analytics.SegmentUsageTracker attribute) (nannyml.usage_logging.SegmentUsageTracker attribute)

WRITE_PICKLE (nannyml.usage_logging.UsageEvent attribute) WRITE_RAW (nannyml.usage_logging.UsageEvent attribute) Writer (class in nannyml.io.base) WriterConfig (class in nannyml.config) WriterException WriterFactory (class in nannyml.io.base)

Y

y_pred (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationAccuracy attribute) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationBusinessValue attribute) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationConfusionMatrix attribute) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationF1 attribute) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationPrecision attribute) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationRecall attribute) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationSpecificity attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationAccuracy attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationBusinessValue attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationConfusionMatrix attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationF1 attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationPrecision attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationRecall attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationSpecificity attribute) (nannyml.performance_calculation.metrics.regression.MAE attribute) (nannyml.performance_calculation.metrics.regression.MAPE attribute) (nannyml.performance_calculation.metrics.regression.MSE attribute) (nannyml.performance_calculation.metrics.regression.MSLE attribute) (nannyml.performance_calculation.metrics.regression.RMSE attribute) (nannyml.performance_calculation.metrics.regression.RMSLE attribute) y_pred_proba (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationAP attribute) (nannyml.performance_calculation.metrics.binary_classification.BinaryClassificationAUROC attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationAccuracy attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationAP attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationAUROC attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationBusinessValue attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationConfusionMatrix attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationF1 attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationPrecision attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationRecall attribute) (nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationSpecificity attribute) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationAccuracy attribute) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationAP attribute) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationAUROC attribute) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationBusinessValue attribute) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationConfusionMatrix attribute) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationF1 attribute) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationPrecision attribute) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationRecall attribute) (nannyml.performance_estimation.confidence_based.metrics.BinaryClassificationSpecificity attribute) (nannyml.performance_estimation.confidence_based.metrics.MulticlassClassificationBusinessValue attribute) (nannyml.performance_estimation.confidence_based.metrics.MulticlassClassificationConfusionMatrix attribute)