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.
yhat(X.model, newdata, ...) # S3 method for lm yhat(X.model, newdata, ...) # S3 method for svm yhat(X.model, newdata, ...) # S3 method for randomForest yhat(X.model, newdata, ...) # S3 method for ranger yhat(X.model, newdata, ...) # S3 method for default yhat(X.model, newdata, ...)
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 |
An numeric matrix of predictions. Can have more than one collumn.
We use the `yhat` name instead of `predict` since we need different defaults that the one set in the `predict` function.