API Reference#
This is the class and function reference of scikit-learn. Please refer to the full user guide for further details, as the raw specifications of classes and functions may not be enough to give full guidelines on their uses. For reference on concepts repeated across the API, see Glossary of Common Terms and API Elements.
Object |
Description |
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Print useful debugging information |
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Plot the elbow curve for different values of K in KMeans clustering. |
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Generates the Cumulative Gains Plot from labels and scores/probabilities. |
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Generate a Lift Curve from true labels and predicted probabilities. |
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Generates the KS Statistic plot from labels and scores/probabilities. |
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Plots PCA components’ explained variance ratios. (new in v0.2.2) |
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Plots the 2-dimensional projection of PCA on a given dataset. |
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Generates a plot of a sklearn model’s feature importances. |
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Generates a plot of the train and test learning curves for a classifier. |
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A legend for the abbreviations of decile table column names. |
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Generates the Decile Table from labels and probabilities |
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Generates the Decile-wise Lift Plot from labels and probabilities |
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Generates the Decile based cumulative Lift Plot from labels and probabilities |
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Generates the Decile-wise Lift Plot from labels and probabilities |
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Generates the KS Statistic Plot from labels and probabilities |
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Generates a decile table and four plots: |
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Plot calibration curves for a set of classifier probability estimates. |
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Generates various evaluation plots for a classifier, including confusion matrix, precision-recall curve, and ROC curve. |
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Generates a confusion matrix plot from predictions and true labels. |
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Generates the ROC AUC curves from labels and predicted scores/probabilities. |
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Generates the Precision-Recall AUC Curves from labels and predicted scores/probabilities. |
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Plots silhouette analysis of clusters provided. |
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Create a model_plots object |
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Plotting response curve |
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Plotting cumulative response curve |
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Plotting cumulative lift curve |
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Plotting cumulative gains curve |
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Plotting cumulative gains curve |
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Plotting costs / revenue curve |
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Plotting profit curve |
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Plotting ROI curve |
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Normalizing input |
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Check if the input matches any of a complete list |
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Combine multiple figures into a single image, save it (if specified), and return the combined figure. |
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Validates the labels passed into arguments such as |
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Generate the data points necessary to plot the Cumulative Gain curve for binary classification tasks. |
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Generate the data points necessary to plot the Kolmogorov-Smirnov (KS) |
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Compute the sigmoid function for the input array x. |
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Compute the softmax function for each row of the input array x. |
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Generates the ROC curves from labels and predicted scores/probabilities |
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Generates the Precision Recall Curve from labels and probabilities |
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This package/module is designed to be compatible with both Python 2 and Python 3. |
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This package/module is designed to be compatible with both Python 2 and Python 3. |
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This package/module is designed to be compatible with both Python 2 and Python 3. |