yhat: Wrap Various Predict Functions

View source: R/misc_yhat.R

yhatR Documentation

Wrap Various Predict Functions

Description

This function is a wrapper over various predict functions for different models and differnt model structures. The wrapper returns a single numeric score for each new observation. To do this it uses different extraction techniques for models from different classes, like for classification random forest is forces the output to be probabilities not classes itself.

Usage

yhat(X.model, newdata, ...)

## S3 method for class 'lm'
yhat(X.model, newdata, ...)

## S3 method for class 'randomForest'
yhat(X.model, newdata, ...)

## S3 method for class 'svm'
yhat(X.model, newdata, ...)

## S3 method for class 'gbm'
yhat(X.model, newdata, ...)

## S3 method for class 'glm'
yhat(X.model, newdata, ...)

## S3 method for class 'cv.glmnet'
yhat(X.model, newdata, ...)

## S3 method for class 'glmnet'
yhat(X.model, newdata, ...)

## S3 method for class 'ranger'
yhat(X.model, newdata, ...)

## S3 method for class 'model_fit'
yhat(X.model, newdata, ...)

## S3 method for class 'train'
yhat(X.model, newdata, ...)

## S3 method for class 'lrm'
yhat(X.model, newdata, ...)

## S3 method for class 'rpart'
yhat(X.model, newdata, ...)

## S3 method for class ''function''
yhat(X.model, newdata, ...)

## S3 method for class 'party'
yhat(X.model, newdata, ...)

## Default S3 method:
yhat(X.model, newdata, ...)

Arguments

X.model

object - a model to be explained

newdata

data.frame or matrix - observations for prediction

...

other parameters that will be passed to the predict function

Details

Currently supported packages are:

  • class cv.glmnet and glmnet - models created with glmnet package,

  • class glm - generalized linear models created with glm,

  • class model_fit - models created with parsnip package,

  • class lm - linear models created with lm,

  • class ranger - models created with ranger package,

  • class randomForest - random forest models created with randomForest package,

  • class svm - support vector machines models created with the e1071 package,

  • class train - models created with caret package,

  • class gbm - models created with gbm package,

  • class lrm - models created with rms package,

  • class rpart - models created with rpart package.

Value

An numeric matrix of predictions


DALEX documentation built on June 16, 2022, 1:06 a.m.

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