Perform (weighted) majority vote prediction from classification Predictions by connecting PipeOpClassifAvg to multiple PipeOpLearner outputs.

If the incoming Learner's $predict_type is set to "response", the prediction obtained is also a "response" prediction with each instance predicted to the prediction from incoming Learners with the highest total weight. If the Learner's$predict_type is set to "prob", the prediction obtained is also a "prob" type prediction with the probability predicted to be a weighted average of incoming predictions.

All incoming Learner's $predict_type must agree. Weights can be set as a parameter; if none are provided, defaults to equal weights for each prediction. Defaults to equal weights for each model. ## Format R6Class inheriting from PipeOpEnsemble/PipeOp. ## Construction PipeOpClassifAvg$new(innum = 0, id = "classifavg", param_vals = list())
• innum :: numeric(1)
Determines the number of input channels. If innum is 0 (default), a vararg input channel is created that can take an arbitrary number of inputs.

• id :: character(1) Identifier of the resulting object, default "classifavg".

• param_vals :: named list
List of hyperparameter settings, overwriting the hyperparameter settings that would otherwise be set during construction. Default list().

## Input and Output Channels

Input and output channels are inherited from PipeOpEnsemble. Instead of a Prediction, a PredictionClassif is used as input and output during prediction.

## Fields

Only fields inherited from PipeOpEnsemble/PipeOp.

## Methods

Only methods inherited from PipeOpEnsemble/PipeOp.