StandardScaler
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@ -5,7 +5,7 @@ import seaborn as sns
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from numpy.random import choice, seed
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from sklearn.decomposition import PCA
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from sklearn.preprocessing import Normalizer
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from sklearn.preprocessing import StandardScaler
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seed(42)
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@ -44,7 +44,7 @@ def is_finished(old_medoids, new_medoids):
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def kmedoids(num_samples, num_clusters):
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df = pd.read_csv('CC GENERAL.csv', index_col='CUST_ID')
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df = df[:num_samples].fillna(0)
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df_scaled = pd.DataFrame(Normalizer().fit_transform(df))
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df_scaled = pd.DataFrame(StandardScaler().fit_transform(df))
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# initialize medoids (at random)
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medoids = initialize_medoids(num_medoids=num_clusters, data=df_scaled)
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