Update Support Vector Regression Position_Salaries.py

Author: jaydipkumar

Support Vector Regression Position_Salaries.py

@@ -1,8 +1,3 @@
-#!/usr/bin/env python
-# coding: utf-8
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-# In[61]:
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 #import libabry
 
@@ -12,46 +7,31 @@
 from sklearn.preprocessing import StandardScaler
 from sklearn.svm import SVR
 
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-# In[62]:
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 #read dataset
 dataset = pd.read_csv('~/Downloads/Data Science/data set/Position_Salaries.csv')
 X = pd.DataFrame(dataset, columns = ['Gender', 'Age'])
 y = pd.DataFrame(dataset, columns = ['EstimatedSalary'])
 
 
-# In[68]:
-
-
 #Feature Scaling
 sc_X = StandardScaler()
 sc_y = StandardScaler()
 X = sc_X.fit_transform(X)
 y = sc_y.fit_transform(y)
 
 
-# In[69]:
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 #build model
 regressor = SVR(kernel = 'rbf')
 regressor.fit(X, y)
 
 
-# In[ ]:
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 #predicte new value
 
 y_pred = regressor.predict(6.5)
 y_pred = sc_y.inverse_transform(y_pred) 
 view raw
 
 
-# In[70]:
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 # Visualize SVR
 X_grid = np.arange(min(X), max(X), 0.01) #this step required because data is feature scaled.
@@ -64,8 +44,3 @@
 plt.show()
 
 
-# In[ ]:
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