【问题标题】:tuning naive Bayes classifier with Caret in R在 R 中使用插入符号调整朴素贝叶斯分类器
【发布时间】:2017-07-04 01:40:00
【问题描述】:

我用以下代码训练模型,但是,我不知道如何更改 tunegrid,因为 FL 和 Adjust 一直保持在特定值。(我的数据集是分类的)

Activity_nb <- train(Actx, Acty,data = Dact, method = "nb", trControl =   myc1,metric = "Accuracy",importance = TRUE)
Naive Bayes 

2694 samples
4 predictor
4 classes: 'CC', 'CE', 'CW', 'HA' 

No pre-processing
Resampling: Cross-Validated (10 fold) 
Summary of sample sizes: 2425, 2424, 2426, 2425, 2425, 2423, ... 
Resampling results across tuning parameters:

usekernel  Accuracy   Kappa    
FALSE      0.8165804  0.6702313
TRUE      0.8165804  0.6702313

Tuning parameter 'fL' was held constant at a value of 0
Tuning parameter 'adjust' was held constant at a value of 1
Accuracy was used to select the optimal model using  the largest value.
The final values used for the model were fL = 0, usekernel = FALSE and    adjust = 1.

【问题讨论】:

    标签: r r-caret naivebayes


    【解决方案1】:
    grid <- data.frame(fL=c(0,0.5,1.0), usekernel = TRUE, adjust=c(0,0.5,1.0))
    
    Activity_nb <- train(..., tuneGrid=grid, ...)
    

    希望这会有所帮助。

    【讨论】:

    • 请解释一下
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