Fix numpy random seed

scikit-learn/adaboost_regressor/train.py

@@ -2,6 +2,7 @@
 # -*- coding: utf-8 -*-
 
 import joblib
+import numpy as np
 
 from sklearn.datasets import fetch_california_housing
 from sklearn.ensemble import AdaBoostRegressor
@@ -9,6 +10,7 @@ from sklearn.model_selection import train_test_split
 
 # Set the random seed
 random_seed = 0
+np.random.seed(random_seed)
 
 # Load the dataset
 dataset = fetch_california_housing()

scikit-learn/bayesian_ridge/train.py

@@ -2,6 +2,7 @@
 # -*- coding: utf-8 -*-
 
 import joblib
+import numpy as np
 
 from sklearn.datasets import fetch_california_housing
 from sklearn.linear_model import BayesianRidge
@@ -9,6 +10,7 @@ from sklearn.model_selection import train_test_split
 
 # Set the random seed
 random_seed = 0
+np.random.seed(random_seed)
 
 # Load the dataset
 dataset = fetch_california_housing()

scikit-learn/catboost_regressor/train.py

@@ -2,6 +2,7 @@
 # -*- coding: utf-8 -*-
 
 import joblib
+import numpy as np
 
 from catboost import CatBoostRegressor
 from sklearn.datasets import fetch_california_housing
@@ -9,6 +10,7 @@ from sklearn.model_selection import train_test_split
 
 # Set the random seed
 random_seed = 0
+np.random.seed(random_seed)
 
 # Load the dataset
 dataset = fetch_california_housing()

scikit-learn/gaussian_nb/train.py

@@ -2,6 +2,7 @@
 # -*- coding: utf-8 -*-
 
 import joblib
+import numpy as np
 
 from sklearn.datasets import load_iris
 from sklearn.model_selection import train_test_split
@@ -9,6 +10,7 @@ from sklearn.naive_bayes import GaussianNB
 
 # Set the random seed
 random_seed = 0
+np.random.seed(random_seed)
 
 # Load the dataset
 dataset = load_iris()