fixed merge

.gitignore

@@ -7,3 +7,4 @@ dataset/train.csv
 dataset/*
 src/old_models/
 config/
+.idea/

src/ensemble_log_regression.py

@@ -11,7 +11,13 @@
 
 
 class Config(object):
+<<<<<<< HEAD
+    """Configuration object for the classifiers
+    batch sixe, number of epochs (the amount of time the program goes through de dataset, learning rate is the step
+    of the gradient, the lambda and mode can be either cross-validation or test"""
+=======
     """Contains hyperparameters for the classifiers"""
+>>>>>>> 21a3636a014486ada42b979c3e94de1878fbe7b2
 
     def __init__(self, batch_size, num_epochs, learning_rate, lambda_, mode='cv'):
         self.batch_size = batch_size

src/utils.py

@@ -23,18 +23,12 @@ def create_csv_submission(ids, y_pred, name):
         for r1, r2 in zip(ids, y_pred):
             writer.writerow({'Id': int(r1), 'Prediction': int(r2)})
 
-def xavier_init(size):
-    var = 2/(np.sum(size))
-    return var * np.random.randn(*size)
-
-def adam(theta, m, v, beta_1, beta_2, learning_rate,  gradient, iter_num):
-    m = (beta_1 * m + (1 - beta_1) * gradient)/(1-beta_1**iter_num)
-    v = (beta_2 * v + (1 - beta_2) * gradient**2)/(1-beta_2**iter_num)
-    return theta - learning_rate*m/(v**0.5 + 10**-8), m, v
-
-
 def dataloader(mode='train', reduced=False):
+<<<<<<< HEAD
+    #TODO: erase the reduced feature since it is not used
+=======
     """Load datasets"""
+>>>>>>> 21a3636a014486ada42b979c3e94de1878fbe7b2
     print("Loading data ...")
     file_name = 'dataset/' + mode + '.csv'
     with open(file_name) as f:
@@ -134,6 +128,3 @@ def build_polynomial(x):
 
     base = np.hstack((bias[:, np.newaxis], np.log(abs(1+x)), x, base_mixed, x**2, x**3))
     return base
-
-if __name__ == '__main__':
-    pass