Model cross-validation concept and code summary - Code World

Model cross-validation concept and code summary

Enterprise 2023-07-02 10:56:27 views: null

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Origin blog.csdn.net/weixin_51524504/article/details/130056992

Model cross-validation concept and code summary

Cross-validation (Cross Validation) principle Summary

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Using cross-validation (Cross Validation) for model assessment

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Cross-validation ideas

Keras model for cross validation

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

"Statistical Learning Methods" (Li Hang): model evaluation selection, regularization and cross-validation, generalization ability, generative model and discriminative model, supervised learning application

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

What is cross-validation (Cross Validation)?

[Machine Learning] Cross-validation (Cross Validation)

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