Fixing Model, still normalization problem

1 files changed, 7 insertions, 7 deletions

diff --git a/src/model.py b/src/model.py
index 8fb34a9..ee43050 100644
--- a/src/model.py
+++ b/src/model.py
@@ -1,6 +1,6 @@
 import numpy as np
 import matplotlib.pyplot as plt
-from sklearn.preprocessing import normalize as sklearn_normalize
+import sklearn.preprocessing
 
 
 class Model:
@@ -11,7 +11,7 @@ class Model:
         self.xs, self.ys = self._read_data()
 
     def train(self, alpha=1, epoch=100):
-        self.xs, self.ys = self._normalize_data()
+        self._normalize_data()
         for _ in range(epoch):
             next_theta0 = self.theta0 - alpha * self._partial_theta0()
             next_theta1 = self.theta1 - alpha * self._partial_theta1()
@@ -19,8 +19,8 @@ class Model:
             self.theta1 = next_theta1
 
     def write_theta(self):
-        with open(self.datafilename, "w") as file:
-            file.write("{},{}".format(str(theta1), str(theta0)))
+        with open(self.thetafilename, "w") as file:
+            file.write("{},{}".format(str(self.theta1), str(self.theta0)))
 
     def hypothesis(self, x):
         return x * self.theta1 + self.theta0
@@ -54,7 +54,7 @@ class Model:
                     for x, y in zip(self.xs, self.ys)]) / len(self.xs)
 
     def _normalize_data(self):
-        self.xs, self.ys = sklearn_normalize([self.xs, self.ys])
+        self.xs, self.ys = sklearn.preprocessing.normalize([self.xs, self.ys])
 
     def _read_theta(self):
         try:
@@ -62,13 +62,13 @@ class Model:
                 strs = file.read().strip().split(",")
                 if len(strs) != 2:
                     raise "wrong theta file format"
-                return int(strs[0]), int(strs[1])
+                return float(strs[0]), float(strs[1])
         except IOError:
             print(self.thetafilename, "do not exist")
 
     def _read_data(self):
         try:
-            data = np.genfromtxt(self.datafilename, delimiter=",")
+            data = np.genfromtxt(self.datafilename, delimiter=",")[1:]
             return data[:, 0], data[:, 1]
         except IOError:
             print(self.datafilename, "do not exist")