Web Reference: Apr 25, 2022 · That happens because the class column has to start from 0 (as required since version 1.3.2). An easy way to solve that is using LabelEncoder from sklearn.preprocssing library. May 30, 2023 · How to solve this Error?---ValueError: Invalid classes inferred from unique values of y. Expected: [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13], got ['Afghanistan' 'Australia' 'Bangladesh' 'England' ' Feb 27, 2024 · As one can see, it's not contiguous. The solution is that you should fit the label encoder on the training data instead. The second issue is that, since the label consists of discrete values, you might consider train_test_split(X, y, stratify=y) for properly distributed classes.
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