Model Validation --R language - Code World

Model Validation --R language

Others 2019-07-22 08:38:16 views: null

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Origin www.cnblogs.com/Grayling/p/11223573.html

Model Validation --R language

R language uses the train function of the caret package to build a naive Bayesian model (NB) model to build a classification model, the trainControl function to set cross-validation parameters, and customize tuning evaluation indicators

R language uses the train function of the caret package to build a KNN proximity algorithm model (KNN) model to build a classification model, trainControl function to set cross-validation parameters, and customize tuning evaluation indicators

R language uses the train function of the caret package to build an xgboost model (based on the gbtree algorithm) model to build a classification model, trainControl function to set cross-validation parameters, and customize tuning evaluation indicators

CLASSIFICATION language model R

R language uses the train function of the caret package to build a conditional inference tree model algorithm (ctree) to build a classification model, the trainControl function to set cross-validation parameters, and customize tuning evaluation indicators

R language uses the train function of the caret package to build a penalty discriminant analysis model (pda) to build a classification model, the trainControl function to set cross-validation parameters, and customize tuning evaluation indicators

R language uses the train function of the caret package to build a multi-layer perceptron algorithm model (MLP) to build a classification model, the trainControl function to set cross-validation parameters, and customize tuning evaluation indicators

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