Classification Learner App Iterations

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KF
KF 2021-5-21
回答： Prince Kumar 2022-4-7
Hi,
I am performing supervised learning on a binary data set of 20 samples. I am doing holdout variation, training on 80% and testing on 20% of the data. As 20% of the test data is only 4 samples, the accuracy I get out each time I run a classifier varies wildly. I have found a way to manually add repeat iterations by generating the code from the app and adding it in (I am currently using 1000 iterations). However, I would like to be able to use the optimisable classifiers found in the app, but they would only be valuable if I can find a way to add repeat iterations using different holdout samples for each run. Any help would be much appreciated!

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回答（1 个）

Prince Kumar
Prince Kumar 2022-4-7
Hi,
Your training sample is too small for the model to learn anything significant. If you train your model for large interations, then your model will overfit.
Hope this helps!

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