正则化

线性模型的岭回归、LASSO 和弹性网

为了提高在中低维数据集上的准确度，可以使用 lasso 或 ridge 进行正则化最小二乘回归。

为了减少在高维数据集上的计算时间，可以使用 fitrlinear 拟合正则化线性回归模型。

函数

`lasso`	Lasso or elastic net regularization for linear models
`ridge`	Ridge regression
`lassoPlot`	Trace plot of lasso fit

`fitrlinear`	Fit linear regression model to high-dimensional data
`predict`	Predict response of linear regression model

`RegressionLinear`	Linear regression model for high-dimensional data
`RegressionPartitionedLinear`	Cross-validated linear regression model for high-dimensional data

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.