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Regularización

Regresión ridge, lasso, elastic nets

Para aumentar la precisión en conjuntos de datos de dimensiones bajas y medianas, implemente una regresión de mínimos cuadrados con regularización mediante lasso o ridge.

Para reducir el tiempo de cálculo en conjuntos de datos de altas dimensiones, ajuste un modelo de regresión lineal regularizada mediante fitrlinear.

Funciones

lassoLasso or elastic net regularization for linear models
ridgeRidge regression
lassoPlotTrace plot of lasso fit
fitrlinearFit linear regression model to high-dimensional data
predictPredict response of linear regression model

Clases

RegressionLinearLinear regression model for high-dimensional data
RegressionPartitionedLinearCross-validated linear regression model for high-dimensional data

Temas

Lasso Regularization

See how lasso identifies and discards unnecessary predictors.

Lasso and Elastic Net with Cross Validation

Predict the mileage (MPG) of a car based on its weight, displacement, horsepower, and acceleration using lasso and elastic net.

Wide Data via Lasso and Parallel Computing

Identify important predictors using lasso and cross-validation.

Lasso and Elastic Net

The lasso algorithm is a regularization technique and shrinkage estimator. The related elastic net algorithm is more suitable when predictors are highly correlated.

Ridge Regression

Ridge regression addresses the problem of multicollinearity (correlated model terms) in linear regression problems.