Fix data normalization for knn

src/P1/processing.py

@@ -8,7 +8,7 @@ from sklearn.metrics import confusion_matrix, roc_auc_score, roc_curve
 from sklearn.naive_bayes import GaussianNB
 from sklearn.neighbors import KNeighborsClassifier
 from sklearn.neural_network import MLPClassifier
-from sklearn.preprocessing import scale
+from sklearn.preprocessing import MinMaxScaler
 from sklearn.svm import LinearSVC
 from sklearn.tree import DecisionTreeClassifier
 
@@ -32,7 +32,8 @@ def predict_data(data, target, model, results):
     model_name = model
     model = choose_model(model=model)
     if model_name == "knn":
-        data = scale(data)
+        scaler = MinMaxScaler()
+        data[data.columns] = scaler.fit_transform(data[data.columns])
     confusion_matrices, auc, fpr, tpr = [], [], [], []
     for train_index, test_index in split_k_sets(data):
         model.fit(data.iloc[train_index], target.iloc[train_index])