Create a model whose training part is random forest and its experimental part is binary classificat
Create a model whose training part is random forest and its experimental part is binary classification using cross-validation
Hello friendsI want to implement the model inside the article I attached with Rapid Miner.
But I encountered the following problems:
1- How can I create a model using cross-validation to use random forest in the experimental section and binary classification in the training section? (90% training and 10% experiment)
2. How do I do the Pearson correlation coefficient in Ripper Miner?
3- How to implement the diagram ROC for the desired model?
General structure of the model: