Index A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | R | S | T | U | V | W | X | Z A Accuracy Artificial Intelligence (AI) Aspect Ratio aspect_ratio (dataeval.metrics.stats.DimensionStatsOutput attribute) AUROC Autoencoder Average Pooling B Balance balance (dataeval.metrics.bias.BalanceOutput attribute) Bayes Error Rate (BER) ber (dataeval.metrics.estimators.BEROutput attribute) ber_lower (dataeval.metrics.estimators.BEROutput attribute) Bias Binary Classification Black-box Shift Estimation (BBSE) Blur Bonferroni Correction Brightness brightness (dataeval.metrics.stats.VisualStatsOutput attribute) built-in function dataeval.detectors.drift.preprocess_drift() dataeval.log() dataeval.metrics.bias.balance() dataeval.metrics.bias.coverage() dataeval.metrics.bias.diversity() dataeval.metrics.bias.label_parity() dataeval.metrics.bias.parity() dataeval.metrics.estimators.ber() dataeval.metrics.estimators.divergence() dataeval.metrics.estimators.uap() dataeval.metrics.stats.boxratiostats() dataeval.metrics.stats.channelstats() dataeval.metrics.stats.datasetstats() dataeval.metrics.stats.dimensionstats() dataeval.metrics.stats.hashstats() dataeval.metrics.stats.labelstats() dataeval.metrics.stats.pixelstats() dataeval.metrics.stats.visualstats() dataeval.utils.dataset.read_dataset() dataeval.utils.dataset.split_dataset() dataeval.utils.metadata.merge() dataeval.utils.metadata.preprocess() C Categorical Variable center (dataeval.metrics.stats.DimensionStatsOutput attribute) Channel (Images) channels (dataeval.metrics.stats.DimensionStatsOutput attribute) Chi-Square Test of Independence class_count (dataeval.metrics.stats.LabelStatsOutput attribute) class_labels (dataeval.utils.metadata.Metadata attribute) class_list (dataeval.metrics.bias.BalanceOutput attribute) (dataeval.metrics.bias.DiversityOutput attribute) class_names (dataeval.utils.metadata.Metadata attribute) Classification classwise (dataeval.metrics.bias.BalanceOutput attribute) (dataeval.metrics.bias.DiversityOutput attribute) Cluster Analysis Concept Drift Confidence Level Confusion Matrix continuous_data (dataeval.utils.metadata.Metadata attribute) continuous_factor_names (dataeval.utils.metadata.Metadata attribute) Contractive Autoencoder (CAE) contrast (dataeval.metrics.stats.VisualStatsOutput attribute) Convolutional Layer Convolutional Neural Network (CNN) Coverage Cramér-von Mises (CVM) Drift Detection critical_value (dataeval.metrics.bias.CoverageOutput attribute) D darkness (dataeval.metrics.stats.VisualStatsOutput attribute) DataEval dataeval module dataeval.detectors module dataeval.detectors.drift module dataeval.detectors.drift.DriftCVM (built-in class) dataeval.detectors.drift.DriftKS (built-in class) dataeval.detectors.drift.DriftMMD (built-in class) dataeval.detectors.drift.DriftMMDOutput (built-in class) dataeval.detectors.drift.DriftOutput (built-in class) dataeval.detectors.drift.DriftUncertainty (built-in class) dataeval.detectors.drift.preprocess_drift() built-in function dataeval.detectors.drift.updates module dataeval.detectors.drift.updates.LastSeenUpdate (built-in class) dataeval.detectors.drift.updates.ReservoirSamplingUpdate (built-in class) dataeval.detectors.linters module dataeval.detectors.linters.Clusterer (built-in class) dataeval.detectors.linters.ClustererOutput (built-in class) dataeval.detectors.linters.Duplicates (built-in class) dataeval.detectors.linters.DuplicatesOutput (built-in class) dataeval.detectors.linters.Outliers (built-in class) dataeval.detectors.linters.OutliersOutput (built-in class) dataeval.detectors.ood module dataeval.detectors.ood.OOD_AE (built-in class) dataeval.detectors.ood.OODOutput (built-in class) dataeval.detectors.ood.OODScoreOutput (built-in class) dataeval.log() built-in function dataeval.metrics module dataeval.metrics.bias module dataeval.metrics.bias.balance() built-in function dataeval.metrics.bias.BalanceOutput (built-in class) dataeval.metrics.bias.coverage() built-in function dataeval.metrics.bias.CoverageOutput (built-in class) dataeval.metrics.bias.diversity() built-in function dataeval.metrics.bias.DiversityOutput (built-in class) dataeval.metrics.bias.label_parity() built-in function dataeval.metrics.bias.parity() built-in function dataeval.metrics.bias.ParityOutput (built-in class) dataeval.metrics.estimators module dataeval.metrics.estimators.ber() built-in function dataeval.metrics.estimators.BEROutput (built-in class) dataeval.metrics.estimators.divergence() built-in function dataeval.metrics.estimators.DivergenceOutput (built-in class) dataeval.metrics.estimators.uap() built-in function dataeval.metrics.estimators.UAPOutput (built-in class) dataeval.metrics.stats module dataeval.metrics.stats.boxratiostats() built-in function dataeval.metrics.stats.channelstats() built-in function dataeval.metrics.stats.ChannelStatsOutput (built-in class) dataeval.metrics.stats.datasetstats() built-in function dataeval.metrics.stats.DatasetStatsOutput (built-in class) dataeval.metrics.stats.dimensionstats() built-in function dataeval.metrics.stats.DimensionStatsOutput (built-in class) dataeval.metrics.stats.hashstats() built-in function dataeval.metrics.stats.HashStatsOutput (built-in class) dataeval.metrics.stats.labelstats() built-in function dataeval.metrics.stats.LabelStatsOutput (built-in class) dataeval.metrics.stats.pixelstats() built-in function dataeval.metrics.stats.PixelStatsOutput (built-in class) dataeval.metrics.stats.visualstats() built-in function dataeval.metrics.stats.VisualStatsOutput (built-in class) dataeval.utils module dataeval.utils.dataset module dataeval.utils.dataset.datasets module dataeval.utils.dataset.datasets.MNIST (built-in class) dataeval.utils.dataset.read_dataset() built-in function dataeval.utils.dataset.split_dataset() built-in function dataeval.utils.dataset.SplitDatasetOutput (built-in class) dataeval.utils.metadata module dataeval.utils.metadata.merge() built-in function dataeval.utils.metadata.Metadata (built-in class) dataeval.utils.metadata.preprocess() built-in function dataeval.utils.torch module dataeval.utils.torch.models module dataeval.utils.torch.models.Autoencoder (built-in class) dataeval.utils.torch.models.Decoder (built-in class) dataeval.utils.torch.models.Encoder (built-in class) dataeval.utils.torch.trainer module dataeval.utils.torch.trainer.AETrainer (built-in class) dataeval.workflows module dataeval.workflows.Sufficiency (built-in class) dataeval.workflows.SufficiencyOutput (built-in class) Dataset Splits Deduplication Deep Neural Network (DNN) Denoising Autoencoder (DAE) depth (dataeval.metrics.stats.DimensionStatsOutput attribute) Developmental Dataset Dimensionality Reduction dimensionstats (dataeval.metrics.stats.DatasetStatsOutput attribute) discrete_data (dataeval.utils.metadata.Metadata attribute) discrete_factor_names (dataeval.utils.metadata.Metadata attribute) distance (dataeval.detectors.drift.DriftMMDOutput attribute) (dataeval.metrics.stats.DimensionStatsOutput attribute) distance_threshold (dataeval.detectors.drift.DriftMMDOutput attribute) distances (dataeval.detectors.drift.DriftOutput attribute) Divergence divergence (dataeval.metrics.estimators.DivergenceOutput attribute) Diversity diversity_index (dataeval.metrics.bias.DiversityOutput attribute) Drift Duplicates duplicates (dataeval.detectors.linters.ClustererOutput attribute) E Embeddings encode() (dataeval.utils.torch.models.Autoencoder method) (dataeval.utils.torch.trainer.AETrainer method) entropy (dataeval.metrics.stats.PixelStatsOutput attribute) Epoch errors (dataeval.metrics.estimators.DivergenceOutput attribute) eval() (dataeval.utils.torch.trainer.AETrainer method) evaluate() (dataeval.detectors.linters.Clusterer method) (dataeval.detectors.linters.Duplicates method) (dataeval.detectors.linters.Outliers method) (dataeval.workflows.Sufficiency method) exact (dataeval.detectors.linters.DuplicatesOutput attribute) F F1-Score factor_names (dataeval.metrics.bias.BalanceOutput attribute) (dataeval.metrics.bias.DiversityOutput attribute) factors (dataeval.metrics.bias.BalanceOutput attribute) False Discovery Rate (FDR) (FDR) False Negative Rate (FN) False Positive Rate (FP) FB Score Feasibility feature_drift (dataeval.detectors.drift.DriftOutput attribute) feature_score (dataeval.detectors.ood.OODOutput attribute) feature_threshold (dataeval.detectors.drift.DriftOutput attribute) find_duplicates() (dataeval.detectors.linters.Clusterer method) find_outliers() (dataeval.detectors.linters.Clusterer method) fit() (dataeval.detectors.ood.OOD_AE method) folds (dataeval.utils.dataset.SplitDatasetOutput attribute) forward() (dataeval.utils.torch.models.Autoencoder method) (dataeval.utils.torch.models.Decoder method) (dataeval.utils.torch.models.Encoder method) from_stats() (dataeval.detectors.linters.Duplicates method) (dataeval.detectors.linters.Outliers method) Fully-Connected Layer G Generative Model get() (dataeval.detectors.ood.OODScoreOutput method) H Hamming Distance height (dataeval.metrics.stats.DimensionStatsOutput attribute) Hilbert Space histogram (dataeval.metrics.stats.PixelStatsOutput attribute) I Image Size image_count (dataeval.metrics.stats.LabelStatsOutput attribute) image_counts_per_label (dataeval.metrics.stats.LabelStatsOutput attribute) image_indices_per_label (dataeval.metrics.stats.LabelStatsOutput attribute) indices (dataeval.metrics.bias.CoverageOutput attribute) Inference instance_score (dataeval.detectors.ood.OODOutput attribute) inv_project() (dataeval.workflows.SufficiencyOutput method) Irreducible Error is_drift (dataeval.detectors.drift.DriftMMDOutput attribute) (dataeval.detectors.drift.DriftOutput attribute) is_ood (dataeval.detectors.ood.OODOutput attribute) issues (dataeval.detectors.linters.OutliersOutput attribute) J Joint Sample K Kolmogorov-Smirnov (K-S) Test kurtosis (dataeval.metrics.stats.PixelStatsOutput attribute) L Label Parity Label Shift label_count (dataeval.metrics.stats.LabelStatsOutput attribute) label_counts_per_class (dataeval.metrics.stats.LabelStatsOutput attribute) label_counts_per_image (dataeval.metrics.stats.LabelStatsOutput attribute) labelstats (dataeval.metrics.stats.DatasetStatsOutput attribute) Laplacian Filter Latent Space left (dataeval.metrics.stats.DimensionStatsOutput attribute) Linter M Machine Learning (ML) Manifold Maximum Mean Discrepancy (MMD) Drift Detection Maximum Pooling mean (dataeval.metrics.stats.PixelStatsOutput attribute) Mean Average Precision measures (dataeval.workflows.SufficiencyOutput attribute) metadata_names (dataeval.metrics.bias.ParityOutput attribute) Minimum Pooling missing (dataeval.metrics.stats.VisualStatsOutput attribute) Modular AI Trustworthy Engineering (MAITE) module dataeval dataeval.detectors dataeval.detectors.drift dataeval.detectors.drift.updates dataeval.detectors.linters dataeval.detectors.ood dataeval.metrics dataeval.metrics.bias dataeval.metrics.estimators dataeval.metrics.stats dataeval.utils dataeval.utils.dataset dataeval.utils.dataset.datasets dataeval.utils.metadata dataeval.utils.torch dataeval.utils.torch.models dataeval.utils.torch.trainer dataeval.workflows Mutual Information (MI) N near (dataeval.detectors.linters.DuplicatesOutput attribute) Neural Network Null Hypothesis NumPy O Object Detection Operational Dataset Operational Drift Out-of-distribution (OOD) Outlier Detection outliers (dataeval.detectors.linters.ClustererOutput attribute) Outliers (Images) Overfitting P P-Value p_val (dataeval.detectors.drift.DriftMMDOutput attribute) p_vals (dataeval.detectors.drift.DriftOutput attribute) p_value (dataeval.metrics.bias.ParityOutput attribute) params (dataeval.workflows.SufficiencyOutput attribute) Parity pchash (dataeval.metrics.stats.HashStatsOutput attribute) percentiles (dataeval.metrics.stats.VisualStatsOutput attribute) Perception-based Hash pixelstats (dataeval.metrics.stats.ChannelStatsOutput attribute) (dataeval.metrics.stats.DatasetStatsOutput attribute) plot() (dataeval.metrics.bias.BalanceOutput method) (dataeval.metrics.bias.CoverageOutput method) (dataeval.metrics.bias.DiversityOutput method) (dataeval.workflows.SufficiencyOutput method) Pooling Layer potential_duplicates (dataeval.detectors.linters.ClustererOutput attribute) potential_outliers (dataeval.detectors.linters.ClustererOutput attribute) Precision Precision Recall Curve predict() (dataeval.detectors.drift.DriftMMD method) (dataeval.detectors.drift.DriftUncertainty method) Principal Component Analysis (PCA) Probability Distribution project() (dataeval.workflows.SufficiencyOutput method) R radii (dataeval.metrics.bias.CoverageOutput attribute) Recall Receiver Operating Characteristic Curve Regularized Autoencoder Riemannian Manifold ROC Curve S score (dataeval.metrics.bias.ParityOutput attribute) score() (dataeval.detectors.drift.DriftCVM method) (dataeval.detectors.drift.DriftKS method) (dataeval.detectors.drift.DriftMMD method) sharpness (dataeval.metrics.stats.VisualStatsOutput attribute) size (dataeval.metrics.stats.DimensionStatsOutput attribute) skew (dataeval.metrics.stats.PixelStatsOutput attribute) Sparse Autoencoder (SAE) Statistical Independence Statistical Manifold Statistics stats (dataeval.detectors.linters.Duplicates attribute) (dataeval.detectors.linters.Outliers attribute) std (dataeval.metrics.stats.PixelStatsOutput attribute) steps (dataeval.workflows.SufficiencyOutput attribute) Sufficiency Supervised Learning T TensorFlow test (dataeval.utils.dataset.SplitDatasetOutput attribute) threshold (dataeval.detectors.drift.DriftMMDOutput attribute) (dataeval.detectors.drift.DriftOutput attribute) top (dataeval.metrics.stats.DimensionStatsOutput attribute) Torch (PyTorch) total_num_factors (dataeval.utils.metadata.Metadata attribute) train() (dataeval.utils.torch.trainer.AETrainer method) True Negative Rate (TN) True Positive Rate (TP) U uap (dataeval.metrics.estimators.UAPOutput attribute) Unsupervised Learning Upper-bound Average Precision (UAP) V var (dataeval.metrics.stats.PixelStatsOutput attribute) Variance Variational Autoencoder: (VAE) visualstats (dataeval.metrics.stats.ChannelStatsOutput attribute) (dataeval.metrics.stats.DatasetStatsOutput attribute) W width (dataeval.metrics.stats.DimensionStatsOutput attribute) X xxhash (dataeval.metrics.stats.HashStatsOutput attribute) Z zeros (dataeval.metrics.stats.VisualStatsOutput attribute)
