loss.biglasso: Internal biglasso functions
In biglasso: Extending Lasso Model Fitting to Big Data

loss.biglasso

R Documentation

Internal biglasso functions

Description

Internal biglasso functions

Usage

loss.biglasso(y, yhat, family, eval.metric, grouped = TRUE)

Arguments

`y`	The observed response vector.
`yhat`	The predicted response vector.
`family`	Either "gaussian" or "binomial", depending on the response.
`eval.metric`	The evaluation metric for the cross-validated error and for choosing optimal `lambda`. "default" for linear regression is MSE (mean squared error), for logistic regression is misclassification error. "MAPE", for linear regression only, is the Mean Absolute Percentage Error. "auc", for logistic regression, is the area under the receiver operating characteristic curve (ROC).
`grouped`	Whether to calculate loss for the entire CV fold (`TRUE`), or for predictions individually. Must be `TRUE` when `eval.metric` is 'auc'.

Details

These are not intended for use by users. loss.biglasso calculates the value of the loss function for the given predictions (used for cross-validation).