cuml.metrics

Classification and Distance Metrics

accuracy_score	Accuracy classification score.
confusion_matrix	Compute confusion matrix to evaluate the accuracy of a classification.
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	Log loss, aka logistic loss or cross-entropy loss.
roc_auc_score	Compute Area Under the Receiver Operating Characteristic Curve (ROC AUC) from prediction scores.
precision_recall_curve	Compute precision-recall pairs for different probability thresholds
trustworthiness	Expresses to what extent the local structure is retained in embedding.

Regression Metrics

mean_absolute_error	Mean absolute error regression loss
mean_squared_error	Mean squared error regression loss
mean_squared_log_error	Mean squared log error regression loss
median_absolute_error	Median absolute error regression loss.
r2_score	\(R^2\) (coefficient of determination) regression score function.

Clustering Metrics

cluster.adjusted_rand_score	Adjusted_rand_score is a clustering similarity metric based on the Rand index and is corrected for chance.
cluster.entropy	cython_entropy(clustering, base=None) -> float
cluster.homogeneity_score	cython_homogeneity_score(labels_true, labels_pred) -> float
cluster.silhouette_score	Calculate the mean silhouette coefficient for the provided data.
cluster.silhouette_samples	Calculate the silhouette coefficient for each sample in the provided data.
cluster.completeness_score	cython_completeness_score(labels_true, labels_pred) -> float
cluster.mutual_info_score	cython_mutual_info_score(labels_true, labels_pred) -> float
cluster.v_measure_score	cython_v_measure(labels_true, labels_pred, beta=1.0) -> float

Pairwise Distances and Kernels

pairwise_distances	Compute the distance matrix from a vector array X and optional Y.
sparse_pairwise_distances	Compute the distance matrix from a vector array X and optional Y.
nan_euclidean_distances	Calculate the euclidean distances in the presence of missing values.
pairwise_kernels	Compute the kernel between arrays X and optional array Y.