diff options
Diffstat (limited to 'src/model.py')
| -rw-r--r-- | src/model.py | 17 |
1 files changed, 7 insertions, 10 deletions
diff --git a/src/model.py b/src/model.py index ee43050..0d74a69 100644 --- a/src/model.py +++ b/src/model.py @@ -1,6 +1,5 @@ import numpy as np import matplotlib.pyplot as plt -import sklearn.preprocessing class Model: @@ -25,6 +24,10 @@ class Model: def hypothesis(self, x): return x * self.theta1 + self.theta0 + def make_prediction(self, predict): + predict = (predict - self.xs.min()) / (self.xs.max() - self.xs.min()) + return self.hypothesis(predict) + def cost(self): return (1 / (2 * len(self.xs))) * sum([(self.hypothesis(x) - y) ** 2 for x, y in zip(self.xs, self.ys)]) @@ -42,8 +45,8 @@ class Model: def _plot_model(self): line_xs = [self.xs.min(), self.xs.max()] - line_ys = [self.hypothesis(x) for x in line_xs] - self.ax.plot(line_xs, line_ys) + line_ys = [self.make_prediction(x) for x in line_xs] + self.ax.plot(line_xs, line_ys, color='r') def _partial_theta1(self): return sum([(self.hypothesis(x) - y) * x @@ -54,7 +57,7 @@ class Model: for x, y in zip(self.xs, self.ys)]) / len(self.xs) def _normalize_data(self): - self.xs, self.ys = sklearn.preprocessing.normalize([self.xs, self.ys]) + self.xs = (self.xs - self.xs.min()) / (self.xs.max() - self.xs.min()) def _read_theta(self): try: @@ -72,9 +75,3 @@ class Model: return data[:, 0], data[:, 1] except IOError: print(self.datafilename, "do not exist") - - -if __name__ == "__main__": - m = Model() - m.train() - m.write_theta() |