iterative_train_test_split is briefly documented here (at the bottom), but the input params X, y are not explained. I tried passing yas a list of lists, encoding the labels as categorical integers, eg
Hello, I have a CSV file that has 9 features and 9 expected targets, and I want to test 2 regression models on this data (that should be generated as a stream).
When I test the MultiTargetRegressionHoeffdingTree and RegressorChain on this data I get a bad R2-score, but when I tried normalizing my data with scikit-learn I get a pretty good R2-score. The problem is that I should not use sci
It is not obvious for now what algorithms should be included in scikit-mine.
My first attempt defining this would be to say we hope for MDL-based algorithms to be included, but that's certainly not sufficient.
Suggest a potential alternative/fix
We should add a dedicated paragraph in the doc, like the one in [scikit-learn doc](https:/
Clasificador de imagenes de bananas, naranjas y limones por medio de algoritmos de aprendizaje K-nn y K-means. Procesado de imágenes con SciKit y OpenCV.
iterative_train_test_splitis briefly documented here (at the bottom), but the input paramsX,yare not explained. I tried passingyas a list of lists, encoding the labels as categorical integers, eg[[2], [0,3], [1], [0,2,3]]but it cras