yhat: Wrapper over the predict function

In DALEXtra: Extension for 'DALEX' Package

Wrapper over the predict function

Description

These functions are default predict functions. Each function returns a single numeric score for each new observation. Those functions are very important since information from many models have to be extracted with various techniques.

Usage

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

## S3 method for class 'H2ORegressionModel'
yhat(X.model, newdata, ...)

## S3 method for class 'H2OBinomialModel'
yhat(X.model, newdata, ...)

## S3 method for class 'H2OMultinomialModel'
yhat(X.model, newdata, ...)

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

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

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

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

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

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

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

## S3 method for class 'model_stack'
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:

• mlr see more in explain_mlr

• h2o see more in explain_h2o

• scikit-learn see more in explain_scikitlearn

• keras see more in explain_keras

• mlr3 see more in explain_mlr3

• xgboost see more in explain_xgboost

• tidymodels see more in explain_tidymodels

Value

An numeric vector of predictions

DALEXtra documentation built on May 31, 2023, 5:30 p.m.