please code in python  Build the pipeline that uses a Principal Component Analysis (PCA) model to extract 2 principal components of the training set and create a a Random Forest model that consists of 50 base decision trees (same as the model in 2D). Fill in the myPCARF function, which accepts as input the training set and returns a fully trained model. Template: def myPCARF(Xtrain, ytrain):     #write function here           return myPCARF You can use any sample dataset

C++ Programming: From Problem Analysis to Program Design
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ISBN:9781337102087
Author:D. S. Malik
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please code in python 
Build the pipeline that uses a Principal Component Analysis (PCA) model to extract 2 principal components of the training set and create a a Random Forest model that consists of 50 base decision trees (same as the model in 2D). Fill in the myPCARF function, which accepts as input the training set and returns a fully trained model.

Template:
def myPCARF(Xtrain, ytrain):
    #write function here 
    
    return myPCARF

You can use any sample dataset

 

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