Add fit_predict to FactorizationMachine

fastFM/base.py

@@ -100,6 +100,27 @@ def predict(self, X_test):
         assert sp.isspmatrix_csc(X_test)
         assert X_test.shape[1] == len(self.w_)
         return ffm.ffm_predict(self.w0_, self.w_, self.V_, X_test)
+
+    def fit_predict(self, X_train, y_train, X_test, n_more_iter=0):
+        """Return predictions after calling fit method
+
+        Parameters
+        ----------
+        X_train : scipy.sparse.csc_matrix, (n_samples, n_features)
+
+        y_train : array, shape (n_samples)
+
+        X_test : scipy.sparse.csc_matrix, (n_test_samples, n_features)
+
+        n_more_iter : int
+                Number of iterations to continue from the current Coefficients.
+
+        Returns
+        -------
+        T : array, shape (n_test_samples)
+        """
+        self.fit(X_train, y_train, n_more_iter=n_more_iter)
+        return self.predict(X_test)
 
 
 class BaseFMClassifier(FactorizationMachine, ClassifierMixin):