Main Content


Train interpretable regression models and interpret complex regression models

Use inherently interpretable regression models, such as linear models, decision trees, and generalized additive models, or use interpretability features to interpret complex regression models that are not inherently interpretable.

To learn how to interpret regression models, see Interpret Machine Learning Models.


expand all

Local Interpretable Model-Agnostic Explanations (LIME)

limeLocal interpretable model-agnostic explanations (LIME)
fitFit simple model of local interpretable model-agnostic explanations (LIME)
plotPlot results of local interpretable model-agnostic explanations (LIME)

Shapley Values

shapleyShapley values
fitCompute Shapley values for query point
plotPlot Shapley values

Partial Dependence

partialDependenceCompute partial dependence
plotPartialDependenceCreate partial dependence plot (PDP) and individual conditional expectation (ICE) plots
fitlmFit linear regression model
fitrgamFit generalized additive model (GAM) for regression
fitrlinearFit linear regression model to high-dimensional data
fitrtreeFit binary decision tree for regression


LinearModelLinear regression model
RegressionGAMGeneralized additive model (GAM) for regression
RegressionLinearLinear regression model for high-dimensional data
RegressionTreeRegression tree


Model Interpretation

Interpretable Models