I have a problem that I can not get to solve.
I have two classes, class 1 deals with the view, class 2 with the calculation.
Class 1 accesses class 2. In class 1 is an instance of class 2 to access the predict method. The method predict has one argument. I set this argument over the input field in class 1. Then this error always occurs : AttributeError: 'float' object has no attribute 'dot' : return X.dot(self.W) + self.b Error when i push the button
Class 1:
class Example1:
self.linearregression = LinearRegression(self,None)
test = tk.DoubleVar(self)
test.set("1.0")
self.predictbutton = ttk.Button(self.plotframe, text = "predict", command = lambda:self.linearregression.predict(test.get()))
self.predictbutton.grid(row=1, column=0)
Class 2:
class LinearRegression():
def __init__(self, learning_rate, iterations):
self.learning_rate = learning_rate
self.iterations = iterations
# Function for model training
def fit(self, X, Y):
# no_of_training_examples, no_of_features
self.m, self.n = X.shape
# weight initialization
self.W = np.zeros(self.n)
self.b = 0
self.X = X
self.Y = Y
# gradient descent learning
for i in range(self.iterations):
self.update_weights()
return self
# Helper function to update weights in gradient descent
def update_weights(self):
Y_pred = self.predict(self.X)
# calculate gradients
dW = - (2 * (self.X.T).dot(self.Y - Y_pred)) / self.m
db = - 2 * np.sum(self.Y - Y_pred) / self.m
# update weights
self.W = self.W - self.learning_rate * dW
self.b = self.b - self.learning_rate * db
return self
# Hypothetical function h( x )
def predict(self, X):
return X.dot(self.W) + self.b
