best: rm age + log(age)

hw2/best.py

@@ -29,12 +29,13 @@ def makeValidation(X, Y):
 Y_train = Y_train.reshape(Y_train.shape[0]) #shape: (32561,)
 
 ## X_train select
+one = [i for i in range(1, X_test.shape[1])]
 square = [0, 1, 3, 4, 5]
 cubic = [0, 1, 3, 4, 5]
-X_train = np.concatenate((X_train,
+X_train = np.concatenate((X_train[:, one],
  X_train[:, square]**2,
  X_train[:, cubic]**3,
- np.log(X_train[:, [0, 3]] + 1e-100)), axis=1)
+ np.log(X_train[:, [3]] + 1e-100)), axis=1)
 
 # scaling: only on features, not label
 mean = np.mean(X_train, axis=0) #shape: (106,)
@@ -100,10 +101,10 @@ def makeValidation(X, Y):
  file.write('id,label\n')
 
  # X_test select
- X_test = np.concatenate((X_test,
+ X_test = np.concatenate((X_test[:, one],
  X_test[:, square]**2,
  X_test[:, cubic]**3,
- np.log(X_test[:, [0, 3]] + 1e-100)), axis=1)
+ np.log(X_test[:, [3]] + 1e-100)), axis=1)
  ans = []
  for i in range(X_test.shape[0]):
  Z = X_test[i]