yhat

yhat.lm

yhat.randomForest

yhat.default

X.model

data.frame or matrix - observations for prediction

newdata

other parameters that will be passed to the `predict` function

This function is just a wrapper over the predict function.
It sets different default parameters for models from different classes.
For example: for classification random Forest is forces the output to be probabilities not classes itself.

Machine Learning models are widely used and have various applications in classification or regression tasks.
Due to increasing computational power, availability of new data sources and new methods, ML models are more and more complex.
Models created with techniques like boosting, bagging of neural networks are true black boxes.
It is hard to trace the link between input variables and model outcomes.
They are used because of high performance, but lack of interpretability is one of their weakest sides.
In many applications we need to know, understand or prove how input variables are used in the model and what impact do they have on final model prediction.
DALEX2 is a collection of tools that help to understand how complex predictive models are working.
DALEX2 is a part of DrWhy universe for tools for Explanation, Exploration and Visualisation for Predictive Models.

yhat: Wrapper over the predict function

Description

Usage

Arguments

Value

Details