- The KFOLD argument was not correctly passed to the "fitctree" function when the model was trained. So, to ensure that the KFOLD argument was passed correctly to the "fitctree" function, you can refer to the following documentation - Fitctree Function
- The KFOLD property was modified after the model was trained or the model was not trained using cross-validation.
Kfold remains 0 after fitting
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why does my kfold be set to 0 after beeing trained and set like that?
mdl = fitctree(T,"HH_kW_01",KFold=7);
mdl
%kfLoss = kfoldLoss(mdl)
display("end");
mdl =
ClassificationPartitionedModel
CrossValidatedModel: 'Discriminant'
PredictorNames: {1×62 cell}
ResponseName: 'HH_kW_01'
NumObservations: 35136
KFold: 0
Partition: [1×1 cvpartition]
ClassNames: [0 0.0049 0.0097 0.0292 0.0312 0.0321 0.0331 0.0351 0.0360 … ]
ScoreTransform: 'none'
Properties, Methods
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回答(1 个)
Piyush Patil
2023-3-3
Hello Huyen,
It seems like the KFOLD property of your ClassificationPartitionedModel object is set to 0. Possible reasons for this to happen could be -
If the issue still persists, then please share the relevant code and information about data files. It will allow me to better understand the issue so that I can assist you in resolving it.
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