biglasso: predict.biglasso – R documentation

Pricing

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

Get Started for Free

Documentation

biglasso

predict.biglasso

Model predictions based on a fitted biglasso object

Description

Extract predictions (fitted reponse, coefficients, etc.) from a fitted biglasso object.

Usage

## S3 method for class 'biglasso'
predict(
  object,
  X,
  row.idx = 1:nrow(X),
  type = c("link", "response", "class", "coefficients", "vars", "nvars"),
  lambda,
  which = 1:length(object$lambda),
  ...
)

## S3 method for class 'biglasso'
coef(object, lambda, which = 1:length(object$lambda), drop = TRUE, ...)

Arguments

`object`	A fitted `"biglasso"` model object.
`X`	Matrix of values at which predictions are to be made. It must be a `big.matrix` object. Not used for `type="coefficients"`.
`row.idx`	Similar to that in `biglasso`, it's a vector of the row indices of `X` that used for the prediction. `1:nrow(X)` by default.
`type`	Type of prediction: `"link"` returns the linear predictors; `"response"` gives the fitted values; `"class"` returns the binomial outcome with the highest probability; `"coefficients"` returns the coefficients; `"vars"` returns a list containing the indices and names of the nonzero variables at each value of `lambda`; `"nvars"` returns the number of nonzero coefficients at each value of `lambda`.
`lambda`	Values of the regularization parameter `lambda` at which predictions are requested. Linear interpolation is used for values of `lambda` not in the sequence of lambda values in the fitted models.
`which`	Indices of the penalty parameter `lambda` at which predictions are required. By default, all indices are returned. If `lambda` is specified, this will override `which`.
`...`	Not used.
`drop`	If coefficients for a single value of `lambda` are to be returned, reduce dimensions to a vector? Setting `drop=FALSE` returns a 1-column matrix.

Value

The object returned depends on type.

Author(s)

Yaohui Zeng and Patrick Breheny

Maintainer: Yaohui Zeng <yaohui.zeng@gmail.com>

Examples

## Logistic regression
data(colon)
X <- colon$X
y <- colon$y
X.bm <- as.big.matrix(X, backingfile = "")
fit <- biglasso(X.bm, y, penalty = 'lasso', family = "binomial")
coef <- coef(fit, lambda=0.05, drop = TRUE)
coef[which(coef != 0)]
predict(fit, X.bm, type="link", lambda=0.05)
predict(fit, X.bm, type="response", lambda=0.05)
predict(fit, X.bm, type="class", lambda=0.1)
predict(fit, type="vars", lambda=c(0.05, 0.1))
predict(fit, type="nvars", lambda=c(0.05, 0.1))

biglasso

Extending Lasso Model Fitting to Big Data

v1.4.1

GPL-3

Authors

Yaohui Zeng [aut,cre], Chuyi Wang [aut,cre], Patrick Breheny [ctb]

Initial release

2021-01-29

predict.biglasso

Description

Usage

Arguments

Value

Author(s)

See Also

Examples

biglasso

We don't support your browser anymore