mactivate (version 0.6.6)

predict.mactivate_fit_gradient_logistic_01: Predict from Fitted Gradient Logistic Model

Description

Predict using fitted model returned by f_fit_gradient_logistic_01.

Usage

# S3 method for mactivate_fit_gradient_logistic_01
predict(object, X0, U0=NULL, mcols, ...)

Arguments

object

A list of class 'mactivate_fit_gradient_logistic_01' as returned by f_fit_gradient_logistic_01().

X0

Numeric matrix, N x d. Model `primary effect' inputs.

U0

Numeric matrix with N rows. Inputs to pass to activation layer.

mcols

Scalar non-negative integer specifying which first columns of W to use.

…

Nothing else is required for this extension of the predict() function.

Value

A named list with 2 elements:

y0hat

Vector of length N. Linear predictions

p0hat

Vector of length N. Probability predictions. Similar to setting type='response' when predicting from glm logistic fitted model

Details

If U0 is not provided, X0 will be passed to activation layer.

See Also

f_fit_gradient_logistic_01.

Examples

# NOT RUN {
####### Please see examples in the fitting functions
# }