스터디노트 (ML5)
📌 LabelEncoder df = pd.DataFrame({ 'A' : ['a', 'b', 'c', 'a', 'b'], 'B' : [1, 2, 3, 1, 0], }) df 📌 Label_encoder - fit -> transform from sklearn.preprocessing import LabelEncoder le = LabelEncoder() le.fit(df['A']) le.classes_ >>>> array(['a', 'b', 'c'], dtype=object) le.transform(df['A']) >>>> array([0, 1, 2, 0, 1]) le.fit_transform(df['A']) >>>> array([0, 1, 2, 0, 1]) le.inverse_transform(df['..
