R language uses deep learning to build a network security intrusion detection system - 코드 세계

R language uses deep learning to build a network security intrusion detection system

프로그래밍 언어 2023-09-16 22:00:03 독서 시간: null

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출처blog.csdn.net/m0_68036862/article/details/132925472

R language uses deep learning to build a network security intrusion detection system

R language uses deep learning to build a network security intrusion detection system

R language uses deep learning to build a network security intrusion detection system

R language uses deep learning to build a network security intrusion detection system

R language uses deep learning to build a network security intrusion detection system

R language uses deep learning to build a network security intrusion detection system

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R language uses the train function of the caret package to build a regularized generalized linear model (glmnet) 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 Bagging AdaBoost model (Bagged AdaBoost) 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

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