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Author: kukr3207

data_scaling.py

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+"@Author: @learn.machinelearning"
+
+from sklearn import preprocessing
+import numpy as np
+
+# Python code for Normalization, Standardization and MinMaxScaler
+# Theory https://www.instagram.com/p/BtQ4csDH083/
+
+vector_A = np.array([[1, 181, 2, 32], [4, 100, 6, 18]])
+#Normalization values
+normalized_X = preprocessing.normalize(vector_A)
+
+#Standardization value
+standardized_X = preprocessing.scale(vector_A)
+
+#MinMaxScaler value
+minmax_X = preprocessing.MinMaxScaler().fit_transform(vector_A)
+print("original data: ", vector_A)
+print("Normalization: ", normalized_X)
+print("Standardization: ", standardized_X)
+print("MinMaxScaler: ", minmax_X)