Similar to other predict methods, this function predicts fitted values from a fitted "MLPRegressor" object.

# S3 method for MLPRegressor
predict(model, data, key, features = NULL, thread.ratio = NULL)

Format

S3 methods

Arguments

model

R6Class object
A 'MLPRegressor' object for prediction.

data

DataFrame
DataFrame containting the data.

key

character
Name of the ID column.

features

character of list of characters, optional
Name of feature columns for prediction.
If not provided, it defaults to all non-key columns of data.

thread.ratio

double, optional
Controls the proportion of available threads that can be used by this function.
The value range is from 0 to 1, where 0 indicates a single thread, and 1 indicates all available threads. Values between 0 and 1 will use up to that percentage of available threads.
Values outside the range from 0 to 1 are ignored, and the actual number of threads used is then be heuristically determined.
Defaults to -1.

Value

DataFrame

  • ID, integer - ID column, with the same name and type as data's ID column

  • TARGET, nvarchar - predicted class name.

  • VALUE, double - softmax value for the predicted class.

Examples

Call the function and predict with a "MLPRegressor" object mplr:


> predict (mplr, data, key = "ID")