【发布时间】:2019-09-29 03:16:59
【问题描述】:
我正在我的数据集上建立一个线性回归模型,但我遇到了一个属性错误,我遇到了一个问题。
class LinearRegressionGD (object):
def _init_(self, eta=0.001, n_iter=20):
self.eta = eta
self.n_iter = n_iter
def fit(self, X, y):
self.w = np.zeros(1 + X.shape[1])
self.cost_ = {}
for i in range(self.n_iter):
output = self.net_input (X)
errors = (y - output)
self.w_[1:] += self.eta * X.T.dot(errors)
self.w_[0] += self.eta * errors.sum()
cost = (errors**2).sum() / 2.0
self.cost_.append(cost)
return self
def net_input(self, X):
return np.dot(X, self.w_[1:]) + self.w_[0]
def predict(self, X):
return self.net_input(X)
X = racing[["BSP"]].values
y = racing[["Position"]].values
from sklearn.preprocessing import StandardScaler
sc_X = StandardScaler()
sc_y = StandardScaler()
X_std = sc_X.fit_transform(X)
y_std = sc_y.fit_transform(y)
lr = LinearRegressionGD()
lr.fit(X_std, y_std)
然后我预计无法绘制结果以查看线性回归是否已经收敛,但我收到以下错误:
AttributeError Traceback (most recent call last)
<ipython-input-23-c876c2ee7b9e> in <module>
----> 1 class LinearRegressionGD (object):
2
3 def _init_(self, eta=0.001, n_iter=20):
4 self.eta = eta
5 self.n_iter = n_iter
<ipython-input-23-c876c2ee7b9e> in LinearRegressionGD()
32 y_std = sc_y.fit_transform(y)
33 lr = LinearRegressionGD()
---> 34 lr.fit(X_std, y_std)
<ipython-input-22-19842f46cb51> in fit(self, X, y)
9 self.cost_ = {}
10
---> 11 for i in range(self.n_iter):
12 output = self.net_input (X)
13 errors = (y - output)
AttributeError: 'LinearRegressionGD' object has no attribute 'n_iter'
【问题讨论】:
标签: python python-3.x scikit-learn linear-regression attributeerror