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 AETrainer (class in dataeval.utils.torch.trainer) AriaAutoencoder (class in dataeval.utils.torch.models) Artificial Intelligence (AI) Aspect Ratio aspect_ratio (dataeval.metrics.stats.DimensionStatsOutput attribute) AUROC Autoencoder Average Pooling B Balance balance (dataeval.metrics.bias.BalanceOutput attribute) balance() (in module dataeval.metrics.bias) BalanceOutput (class in dataeval.metrics.bias) Bayes Error Rate (BER) ber (dataeval.metrics.estimators.BEROutput attribute) ber() (in module dataeval.metrics.estimators) ber_lower (dataeval.metrics.estimators.BEROutput attribute) BEROutput (class in dataeval.metrics.estimators) Bias Binary Classification Black-box Shift Estimation (BBSE) Blur Bonferroni Correction boxratiostats() (in module dataeval.metrics.stats) Brightness brightness (dataeval.metrics.stats.VisualStatsOutput attribute) C Categorical Variable center (dataeval.metrics.stats.DimensionStatsOutput attribute) Channel (Images) channels (dataeval.metrics.stats.DimensionStatsOutput attribute) channelstats() (in module dataeval.metrics.stats) ChannelStatsOutput (class in dataeval.metrics.stats) Chi-Square Test of Independence CIFAR10 (class in dataeval.utils.torch.datasets) class_count (dataeval.metrics.stats.LabelStatsOutput attribute) class_labels (dataeval.metrics.bias.MetadataOutput attribute) class_list (dataeval.metrics.bias.BalanceOutput attribute) (dataeval.metrics.bias.DiversityOutput attribute) class_names (dataeval.metrics.bias.MetadataOutput attribute) Classification classwise (dataeval.metrics.bias.BalanceOutput attribute) (dataeval.metrics.bias.DiversityOutput attribute) Cluster Analysis Clusterer (class in dataeval.detectors.linters) ClustererOutput (class in dataeval.detectors.linters) Concept Drift Confidence Level Confusion Matrix continuous_data (dataeval.metrics.bias.MetadataOutput attribute) continuous_factor_names (dataeval.metrics.bias.MetadataOutput attribute) Contractive Autoencoder (CAE) contrast (dataeval.metrics.stats.VisualStatsOutput attribute) Convolutional Layer Convolutional Neural Network (CNN) Coverage coverage() (in module dataeval.metrics.bias) CoverageOutput (class in dataeval.metrics.bias) Cramér-von Mises (CVM) Drift Detection critical_value (dataeval.metrics.bias.CoverageOutput attribute) D darkness (dataeval.metrics.stats.VisualStatsOutput attribute) DataEval dataeval.detectors module dataeval.detectors.drift module dataeval.detectors.linters module dataeval.detectors.ood module dataeval.metrics module dataeval.metrics.bias module dataeval.metrics.estimators module dataeval.metrics.stats module dataeval.utils module dataeval.utils.torch module dataeval.workflows module Dataset Splits datasetstats() (in module dataeval.metrics.stats) DatasetStatsOutput (class in dataeval.metrics.stats) Decoder (class in dataeval.utils.torch.models) Deduplication Deep Neural Network (DNN) Denoising Autoencoder (DAE) depth (dataeval.metrics.stats.DimensionStatsOutput attribute) Developmental Dataset Dimensionality Reduction dimensionstats (dataeval.metrics.stats.DatasetStatsOutput attribute) dimensionstats() (in module dataeval.metrics.stats) DimensionStatsOutput (class in dataeval.metrics.stats) discrete_data (dataeval.metrics.bias.MetadataOutput attribute) discrete_factor_names (dataeval.metrics.bias.MetadataOutput 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) divergence() (in module dataeval.metrics.estimators) DivergenceOutput (class in dataeval.metrics.estimators) Diversity diversity() (in module dataeval.metrics.bias) diversity_index (dataeval.metrics.bias.DiversityOutput attribute) DiversityOutput (class in dataeval.metrics.bias) Drift DriftCVM (class in dataeval.detectors.drift) DriftKS (class in dataeval.detectors.drift) DriftMMD (class in dataeval.detectors.drift) DriftMMDOutput (class in dataeval.detectors.drift) DriftOutput (class in dataeval.detectors.drift) DriftUncertainty (class in dataeval.detectors.drift) Duplicates (class in dataeval.detectors.linters) duplicates (dataeval.detectors.linters.ClustererOutput attribute) DuplicatesOutput (class in dataeval.detectors.linters) E Embeddings encode() (dataeval.utils.torch.trainer.AETrainer method) Encoder (class in dataeval.utils.torch.models) 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) from_stats() (dataeval.detectors.linters.Duplicates method) (dataeval.detectors.linters.Outliers method) Fully-Connected Layer G Generative Model get() (dataeval.detectors.ood.OODScoreOutput method) get_channel_mask() (dataeval.metrics.stats.DimensionStatsOutput method) (dataeval.metrics.stats.HashStatsOutput method) (dataeval.metrics.stats.PixelStatsOutput method) (dataeval.metrics.stats.VisualStatsOutput method) H Hamming Distance hashstats() (in module dataeval.metrics.stats) HashStatsOutput (class in dataeval.metrics.stats) 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) label_parity() (in module dataeval.metrics.bias) labelstats (dataeval.metrics.stats.DatasetStatsOutput attribute) labelstats() (in module dataeval.metrics.stats) LabelStatsOutput (class in dataeval.metrics.stats) Laplacian Filter LastSeenUpdate (class in dataeval.detectors.drift.updates) 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) merge_metadata() (in module dataeval.utils) metadata_names (dataeval.metrics.bias.ParityOutput attribute) metadata_preprocessing() (in module dataeval.metrics.bias) MetadataOutput (class in dataeval.metrics.bias) Minimum Pooling missing (dataeval.metrics.stats.VisualStatsOutput attribute) MNIST (class in dataeval.utils.torch.datasets) Modular AI Trustworthy Engineering (MAITE) module dataeval.detectors dataeval.detectors.drift dataeval.detectors.linters dataeval.detectors.ood dataeval.metrics dataeval.metrics.bias dataeval.metrics.estimators dataeval.metrics.stats dataeval.utils dataeval.utils.torch dataeval.workflows Mutual Information (MI) N n_features (dataeval.detectors.drift.DriftCVM property) (dataeval.detectors.drift.DriftKS property) near (dataeval.detectors.linters.DuplicatesOutput attribute) Neural Network Null Hypothesis NumPy O Object Detection OOD_AE (class in dataeval.detectors.ood) OODOutput (class in dataeval.detectors.ood) OODScoreOutput (class in dataeval.detectors.ood) Operational Dataset Operational Drift Out-of-distribution (OOD) Outlier Detection Outliers (class in dataeval.detectors.linters) outliers (dataeval.detectors.linters.ClustererOutput attribute) Outliers (Images) OutliersOutput (class in dataeval.detectors.linters) 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 parity() (in module dataeval.metrics.bias) ParityOutput (class in dataeval.metrics.bias) 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) pixelstats() (in module dataeval.metrics.stats) PixelStatsOutput (class in dataeval.metrics.stats) 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.DriftCVM method) (dataeval.detectors.drift.DriftKS method) (dataeval.detectors.drift.DriftMMD method) (dataeval.detectors.drift.DriftUncertainty method) (dataeval.detectors.ood.OOD_AE method) Principal Component Analysis (PCA) Probability Distribution project() (dataeval.workflows.SufficiencyOutput method) R radii (dataeval.metrics.bias.CoverageOutput attribute) read_dataset() (in module dataeval.utils.torch) Recall Receiver Operating Characteristic Curve Regularized Autoencoder ReservoirSamplingUpdate (class in dataeval.detectors.drift.updates) 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) (dataeval.detectors.ood.OOD_AE 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 (class in dataeval.workflows) SufficiencyOutput (class in dataeval.workflows) Supervised Learning T TensorFlow threshold (dataeval.detectors.drift.DriftMMDOutput attribute) (dataeval.detectors.drift.DriftOutput attribute) top (dataeval.metrics.stats.DimensionStatsOutput attribute) Torch (PyTorch) total_num_factors (dataeval.metrics.bias.MetadataOutput attribute) train() (dataeval.utils.torch.trainer.AETrainer method) True Negative Rate (TN) True Positive Rate (TP) U uap (dataeval.metrics.estimators.UAPOutput attribute) uap() (in module dataeval.metrics.estimators) UAPOutput (class in dataeval.metrics.estimators) 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) visualstats() (in module dataeval.metrics.stats) VisualStatsOutput (class in dataeval.metrics.stats) VOCDetection (class in dataeval.utils.torch.datasets) W width (dataeval.metrics.stats.DimensionStatsOutput attribute) X x_ref (dataeval.detectors.drift.DriftCVM property) (dataeval.detectors.drift.DriftKS property) (dataeval.detectors.drift.DriftMMD property) xxhash (dataeval.metrics.stats.HashStatsOutput attribute) Z zeros (dataeval.metrics.stats.VisualStatsOutput attribute)
