Otto Group Product Classification Challenge

Aim: Distinguish between product categories for effective classification.

☑️ What did I do?

• First, I found that there was a class-imbalance problem and that the features were highly skewed.
  • To tackle the class-imbalance problem, I ensured that the ratio of class labels in the variable specified is constant by using the stratify argument in train_test_split.
  • To tackle the skew problem, I used QuantileTransformer.
• I then trained various (7, to be precise) classifier models, ranging from KNN to SVMs to CatBoostClassifier, achieving a multi-class loss below 0.5.

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S.D.G.