predict.L0Learn: Predict Response

In L0Learn: Fast Algorithms for Best Subset Selection

Predict Response

Description

Predicts the response for a given sample.

Usage

## S3 method for class 'L0Learn'
predict(object, newx, lambda = NULL, gamma = NULL, ...)

## S3 method for class 'L0LearnCV'
predict(object, newx, lambda = NULL, gamma = NULL, ...)

Arguments

object	The output of L0Learn.fit or L0Learn.cvfit
newx	A matrix on which predictions are made. The matrix should have p columns.
lambda	The value of lambda to use for prediction. A summary of the lambdas in the regularization path can be obtained using print(fit).
gamma	The value of gamma to use for prediction. A summary of the gammas in the regularization path can be obtained using print(fit).
...	ignore

Value

A Matrix of class dgeMatrix, which contains the model predictions. If both lambda and gamma are not supplied, then a matrix of predictions for all the solutions in the regularization path is returned. If lambda is supplied but gamma is not, the smallest value of gamma is used. In case of logistic regression, probability values are returned.

Examples

# Generate synthetic data for this example
data <- GenSynthetic(n=100,p=20,k=10,seed=1)
X = data$X
y = data$y

# Fit an L0L2 Model with 3 values of Gamma ranging from 0.0001 to 10, using coordinate descent
fit <- L0Learn.fit(X,y, penalty="L0L2", nGamma=3, gammaMin=0.0001, gammaMax = 10)
print(fit)
# Apply the fitted model with lambda=2.45513e-02 and gamma=0.0001 on X to predict the response
predict(fit, newx = X, lambda=2.45513e-02, gamma=0.0001)
# Apply the fitted model on X to predict the response for all the solutions in the path
predict(fit, newx = X)

L0Learn documentation built on March 7, 2023, 8:18 p.m.