Code Documentation: Metrics

mastml.metrics Module

This module contains constructors for different model score metrics. Most model metrics are obtained from scikit-learn, while others are custom variations.

The full list of score functions in scikit-learn can be found at: http://scikit-learn.org/stable/modules/model_evaluation.html

Functions

adjusted_r2_score(y_true, y_pred[, n_features])	Method that calculates the adjusted R^2 value
check_and_fetch_names(metric_names, …)	Method that checks whether chosen metrics to evaluate models are appropriate for user-specified models (e.g.
r2_score_fitted(y_true, y_pred)	Method that calculates the R^2 value
r2_score_noint(y_true, y_pred)	Method that calculates the R^2 value without fitting the y-intercept
rmse_over_stdev(y_true, y_pred[, train_y])	Method that calculates the root mean squared error (RMSE) of a set of data, divided by the standard deviation of the training data set.
root_mean_squared_error(y_true, y_pred)	Method that calculates the root mean squared error (RMSE)