# cuml.metrics ## Classification and Distance Metrics | [`accuracy_score`](../generated/cuml.metrics.accuracy_score/index.html.md#cuml.metrics.accuracy_score) | Accuracy classification score. | |-------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | [`confusion_matrix`](../generated/cuml.metrics.confusion_matrix/index.html.md#cuml.metrics.confusion_matrix) | Compute confusion matrix to evaluate the accuracy of a classification. | | [`kl_divergence`](../generated/cuml.metrics.kl_divergence/index.html.md#cuml.metrics.kl_divergence) | Calculates the "Kullback-Leibler" Divergence The KL divergence tells us how well the probability distribution Q approximates the probability distribution P It is often also used as a 'distance metric' between two probability distributions (not symmetric) | | [`log_loss`](../generated/cuml.metrics.log_loss/index.html.md#cuml.metrics.log_loss) | Log loss, aka logistic loss or cross-entropy loss. | | [`roc_auc_score`](../generated/cuml.metrics.roc_auc_score/index.html.md#cuml.metrics.roc_auc_score) | Compute Area Under the Receiver Operating Characteristic Curve (ROC AUC) from prediction scores. | | [`precision_recall_curve`](../generated/cuml.metrics.precision_recall_curve/index.html.md#cuml.metrics.precision_recall_curve) | Compute precision-recall pairs for different probability thresholds | | [`trustworthiness`](../generated/cuml.metrics.trustworthiness/index.html.md#cuml.metrics.trustworthiness) | trustworthiness(X, X_embedded, n_neighbors=5, metric='euclidean', batch_size=512) -> float | ## Regression Metrics | [`mean_absolute_error`](../generated/cuml.metrics.mean_absolute_error/index.html.md#cuml.metrics.mean_absolute_error) | Mean absolute error regression loss | |-------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------| | [`mean_squared_error`](../generated/cuml.metrics.mean_squared_error/index.html.md#cuml.metrics.mean_squared_error) | Mean squared error regression loss | | [`mean_squared_log_error`](../generated/cuml.metrics.mean_squared_log_error/index.html.md#cuml.metrics.mean_squared_log_error) | Mean squared log error regression loss | | [`median_absolute_error`](../generated/cuml.metrics.median_absolute_error/index.html.md#cuml.metrics.median_absolute_error) | Median absolute error regression loss. | | [`r2_score`](../generated/cuml.metrics.r2_score/index.html.md#cuml.metrics.r2_score) | $R^2$ (coefficient of determination) regression score function. | ## Clustering Metrics | [`cluster.adjusted_rand_score`](../generated/cuml.metrics.cluster.adjusted_rand_score/index.html.md#cuml.metrics.cluster.adjusted_rand_score) | adjusted_rand_score(labels_true, labels_pred) -> float | |-------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------| | [`cluster.entropy`](../generated/cuml.metrics.cluster.entropy/index.html.md#cuml.metrics.cluster.entropy) | cython_entropy(clustering, base=None) -> float | | [`cluster.homogeneity_score`](../generated/cuml.metrics.cluster.homogeneity_score/index.html.md#cuml.metrics.cluster.homogeneity_score) | cython_homogeneity_score(labels_true, labels_pred) -> float | | [`cluster.silhouette_score`](../generated/cuml.metrics.cluster.silhouette_score/index.html.md#cuml.metrics.cluster.silhouette_score) | Calculate the mean silhouette coefficient for the provided data. | | [`cluster.silhouette_samples`](../generated/cuml.metrics.cluster.silhouette_samples/index.html.md#cuml.metrics.cluster.silhouette_samples) | Calculate the silhouette coefficient for each sample in the provided data. | | [`cluster.completeness_score`](../generated/cuml.metrics.cluster.completeness_score/index.html.md#cuml.metrics.cluster.completeness_score) | cython_completeness_score(labels_true, labels_pred) -> float | | [`cluster.mutual_info_score`](../generated/cuml.metrics.cluster.mutual_info_score/index.html.md#cuml.metrics.cluster.mutual_info_score) | cython_mutual_info_score(labels_true, labels_pred) -> float | | [`cluster.v_measure_score`](../generated/cuml.metrics.cluster.v_measure_score/index.html.md#cuml.metrics.cluster.v_measure_score) | cython_v_measure(labels_true, labels_pred, beta=1.0) -> float | ## Pairwise Distances and Kernels | [`pairwise_distances`](../generated/cuml.metrics.pairwise_distances/index.html.md#cuml.metrics.pairwise_distances) | Compute the distance matrix from a feature array X and optional Y. | |---------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------| | [`nan_euclidean_distances`](../generated/cuml.metrics.nan_euclidean_distances/index.html.md#cuml.metrics.nan_euclidean_distances) | Calculate the euclidean distances in the presence of missing values. | | [`pairwise_kernels`](../generated/cuml.metrics.pairwise_kernels/index.html.md#cuml.metrics.pairwise_kernels) | Compute the kernel between arrays X and optional array Y. |