Fix bug

README.md

@@ -30,10 +30,10 @@ Run `pip install git+https://github.com/gbolmier/funk-svd` in your terminal.
 >>> val = df.drop(train.index.tolist()).sample(frac=0.5, random_state=8)
 >>> test = df.drop(train.index.tolist()).drop(val.index.tolist())
 
->>> svd = SVD(lr=0.001, reg=0.005, n_epochs=100, n_factors=15, min_rating=1,
-...           max_rating=5)
+>>> svd = SVD(lr=0.001, reg=0.005, n_epochs=100, n_factors=15,
+...           early_stopping=True, shuffle=False, min_rating=1, max_rating=5)
 
->>> svd.fit(X=train, X_val=val, early_stopping=True, shuffle=False)
+>>> svd.fit(X=train, X_val=val)
 Preprocessing data...
 
 Epoch 1/...

funk_svd/svd.py

@@ -1,4 +1,5 @@
 import numpy as np
+import pandas as pd
 import time
 
 from .fast_methods import _compute_val_metrics
@@ -143,6 +144,10 @@ def _preprocess_data(self, X, train=True):
 
         return X[['u_id', 'i_id', 'rating']].values
 
+    def _init_metrics(self):
+        metrics = np.zeros((self.n_epochs, 3), dtype=np.float)
+        self.metrics_ = pd.DataFrame(metrics, columns=['Loss', 'RMSE', 'MAE'])
+
     def _run_sgd(self, X, X_val):
         """Runs SGD algorithm, learning model weights.
 
@@ -163,15 +168,15 @@ def _run_sgd(self, X, X_val):
         for epoch_ix in range(self.n_epochs):
             start = self._on_epoch_begin(epoch_ix)
 
-            if self.shuffle_:
+            if self.shuffle:
                 X = _shuffle(X)
 
-            pu, qi, bu, bi = _run_epoch(X, bu, bi, pu, qi, self.global_mean_,
+            bu, bi, pu, qi = _run_epoch(X, bu, bi, pu, qi, self.global_mean_,
                                         self.n_factors, self.lr, self.reg)
 
             if X_val is not None:
                 self.metrics_.loc[epoch_ix, :] = _compute_val_metrics(
-                                                     X_val, pu, qi, bu, bi,
+                                                     X_val, bu, bi, pu, qi,
                                                      self.global_mean_,
                                                      self.n_factors
                                                  )
@@ -180,10 +185,10 @@ def _run_sgd(self, X, X_val):
                                    self.metrics_.loc[epoch_ix, 'RMSE'],
                                    self.metrics_.loc[epoch_ix, 'MAE'])
 
-                if self.early_stopping_:
+                if self.early_stopping:
                     val_rmse = self.metrics_['RMSE'].tolist()
                     if self._early_stopping(val_rmse, epoch_ix,
-                                            self.min_delta_):
+                                            self.min_delta):
                         break
 
             else:

funk_svd/utils.py

@@ -26,10 +26,10 @@ def _timer(text=''):
 
     Examples
     --------
-    >>> @timer(text='Greetings took ')
+    >>> @_timer(text='Greetings took ')
     ... def say_hi():
     ...    time.sleep(1)
-    ...    print('Hey! What's up!')
+    ...    print("Hey! What's up!")
     ...
     >>> say_hi()
     Hey! What's up!

run_experiment.py

@@ -10,10 +10,10 @@
 val = df.drop(train.index.tolist()).sample(frac=0.5, random_state=8)
 test = df.drop(train.index.tolist()).drop(val.index.tolist())
 
-svd = SVD(lr=0.001, reg=0.005, n_epochs=100, n_factors=15, min_rating=1,
-          max_rating=5)
+svd = SVD(lr=0.001, reg=0.005, n_epochs=100, n_factors=15, early_stopping=True,
+          shuffle=False, min_rating=1, max_rating=5)
 
-svd.fit(X=train, X_val=val, early_stopping=True, shuffle=False)
+svd.fit(X=train, X_val=val)
 
 pred = svd.predict(test)
 mae = mean_absolute_error(test['rating'], pred)