Code Documentation: Learning Curve

mastml.learning_curve Module

This module contains methods to construct learning curves, which evaluate some cross-validation performance metric (e.g. RMSE) as a function of amount of training data (i.e. a data learning curve) or as a function of the number of features used in the fitting (i.e. a feature learning curve).

LearningCurve:

Class used to construct data learning curves and feature learning curves

Classes

KFold([n_splits, shuffle, random_state])	K-Folds cross-validator
LearningCurve()	This class is used to construct learning curves, both in the form of model performance vs.
Line	Class containing methods for constructing line plots
Metrics(metrics_list[, metrics_type])	Class containing access to a wide range of metrics from scikit-learn and a number of MAST-ML custom-written metrics
SklearnFeatureSelector(selector, **kwargs)	Class that wraps scikit-learn feature selection methods with some new MAST-ML functionality
datetime(year, month, day[, hour[, minute[, …)	The year, month and day arguments are required.

Class Inheritance Diagram