metric_learn package
Module Contents
Base Classes
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Class to build constraints from labeled data. |
Base class for all metric-learners. |
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Base class for all learners that can transform data into a new space with the metric learned. |
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Mahalanobis metric learning algorithms. |
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Base class for pairs learners. |
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Base class for triplets learners. |
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Base class for quadruplets learners. |
Supervised Learning Algorithms
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Local Fisher Discriminant Analysis for Supervised Dimensionality Reduction |
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Large Margin Nearest Neighbor (LMNN) |
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Metric Learning for Kernel Regression (MLKR) |
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Neighborhood Components Analysis (NCA) |
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Relevant Components Analysis (RCA) |
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Supervised version of Information Theoretic Metric Learning (ITML) |
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Supervised version of Least Squared-residual Metric Learning (LSML) |
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Supervised version of Mahalanobis Metric for Clustering (MMC) |
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Supervised version of Sparse Distance Metric Learning (SDML) |
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Supervised version of Relevant Components Analysis (RCA) |
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Supervised version of Sparse Compositional Metric Learning (SCML) |
Weakly Supervised Learning Algorithms
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Information Theoretic Metric Learning (ITML) |
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Least Squared-residual Metric Learning (LSML) |
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Mahalanobis Metric for Clustering (MMC) |
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Sparse Distance Metric Learning (SDML) |
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Sparse Compositional Metric Learning (SCML) |
Unsupervised Learning Algorithms
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Covariance metric (baseline method) |