HIRISE_api.models.metrics

Functions

calculate_metrics(model, labels[, verbose])

Function that calulates metrics including, rand score, adjusted rand score, mutual information score, normalized mutual information score, adjusted mutual information score, balanced accuracy score, completeness score, homogeniety score and v-score for a given model.

classification_metrics_dataframe(model_list, ...)

Fucntion that creates a metrics dataframe based on the calculated metrics for each model in the model list specified by the user.

generate_precision_dataframe(folder_path, ...)

Function that returns a generated a dataframe of all the precision values evaluated for a true and predicted labels after classifiaction analysis on a dataset.

print_confusion_matrix(folder_path, ...[, ...])

Function that prints the confusion matrix metric for a given set of image clustering results and the associated images.