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Author: geekquad

Outliers Removal.py

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+
+# coding: utf-8
+
+# In[20]:
+
+
+import random
+import numpy as np
+import pickle
+import matplotlib.pyplot as plt
+from outlier_cleaner import outlierCleaner
+
+
+# In[22]:
+
+
+ages = pickle.load( open("practice_outliers_ages_modified_unix.pkl", "rb") )
+net_worths = pickle.load( open("practice_outliers_net_worths_modified_unix.pkl", "rb") )
+
+
+# In[31]:
+
+
+ages = np.reshape(np.array(ages), (len(ages), 1))
+new_worths = np.reshape(np.array(net_worths), (len(net_worths), 1))
+
+from sklearn.cross_validation import train_test_split
+ages_train, ages_test, net_worths_train, net_worths_test = train_test_split(ages, net_worths, test_size=0.1, random_state = 42)
+
+
+# In[37]:
+
+
+from sklearn.linear_model import LinearRegression
+reg = LinearRegression()
+reg.fit(ages_train, net_worths_train)
+reg.predict(ages_test)
+print('coef:', reg.coef_)
+print('intercept:', reg.intercept_)
+print('scores:', reg.score(ages_test, net_worths_test))
+