Implementing competing risk model in R language (2)-mstate - 코드 세계

Implementing competing risk model in R language (2)-mstate

프로그래밍 언어 2023-10-04 19:08:27 독서 시간: null

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Implementing competing risk model in R language (2)-mstate

Implementing competing risk model in R language (2)-mstate

R language to implement competing risk model (1)

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R language uses the lift_curve function of the yardstick package to evaluate the performance of the multiclass (Multiclass) model and view the lift curve (lift curve) of the model on each classification of the multiclass.

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 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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