Unbalanced data

[ScottF]

Hi @PrivetPoka -

Here are a couple of recent forum threads that discuss the SMOTE algorithm, which is one way to deal with unbalanced data in KNIME:

SMOTE for unbalanced data

Hello, I have an unballanced data of 7 classes. I read that people recommend SMOTE to balance it without the need to delete samples from oversampled classes. And, indeed, the accuracy of the model that I am generating with random forest or SVM increased significantly. But I feel that this improvement is fake and is kind of cheating. Actually, there 2 options in the SMOTE node ( oversample the whole dataset or oversample the minority). Without SMOTE, the acc = 0.34, with oversampling minority…

Unbalanced data - good practice

Hi Everybody, I have a question concerning treatment of unbalanced data. I am trying to “machine learn” model which should detect corporate credit issues with Random Forest using KNIME. After cleaning the data i have enough records with couple of features but with proportion = 1 issue : 250 not-issue. without any modification i have high (99%) accuracy but all categorized as “not-issue” (no detection of “issue” in validation dataset) - no suprise i suppose i have few feature w…