ValueError: non-broadcastable output operand with shape (1,42) doesn't match the broadcast shape (42,42), when I am using NSL KDD dataset

class SigmoidNeuron:

def init(self): self.w = None self.b = None

def perceptron(self, x): return np.dot(x, self.w.T) + self.b

def sigmoid(self, x): return 1.0/(1.0 + np.exp(-x))

def grad_w_mse(self, x, y): y_pred = self.sigmoid(self.perceptron(x)) return (y_pred - y) * y_pred * (1 - y_pred) * x

def grad_b_mse(self, x, y): y_pred = self.sigmoid(self.perceptron(x)) return (y_pred - y) * y_pred * (1 - y_pred)

def grad_w_ce(self, x, y): y_pred = self.sigmoid(self.perceptron(x)) if y == 0: return y_pred * x elif y == 1: return -1 * (1 - y_pred) * x else: raise ValueError("y should be 0 or 1")

def grad_b_ce(self, x, y): y_pred = self.sigmoid(self.perceptron(x)) if y == 0: return y_pred elif y == 1: return -1 * (1 - y_pred) else: raise ValueError("y should be 0 or 1")

def fit(self, X, Y, epochs=1, learning_rate=1, initialise=True, loss_fn="mse", display_loss=False):

# initialise w, b  if initialise:    self.w = np.random.randn(1, X.shape[1])    self.b = 0      if display_loss:    loss = {}    for i in tqdm_notebook(range(epochs), total=epochs, unit="epoch"):    dw = 0    db = 0    for x, y in zip(X, Y):      if loss_fn == "mse":        dw += self.grad_w_mse(x, y)        db += self.grad_b_mse(x, y)       elif loss_fn == "ce":        dw += self.grad_w_ce(x, y)        db += self.grad_b_ce(x, y)            m = X.shape[1]      self.w -= learning_rate * dw/m    self.b -= learning_rate * db/m        if display_loss:      Y_pred = self.sigmoid(self.perceptron(X))      if loss_fn == "mse":        loss[i] = mean_squared_error(Y, Y_pred)      elif loss_fn == "ce":        loss[i] = log_loss(Y, Y_pred)    if display_loss:    plt.plot(np.array(list(loss.values())).astype(float))    plt.xlabel('Epochs')    if loss_fn == "mse":      plt.ylabel('Mean Squared Error')    elif loss_fn == "ce":      plt.ylabel('Log Loss')    plt.show()      

def predict(self, X): Y_pred = [] for x in X: y_pred = self.sigmoid(self.perceptron(x)) Y_pred.append(y_pred) return np.array(Y_pred)

https://stackoverflow.com/questions/66811338/valueerror-non-broadcastable-output-operand-with-shape-1-42-doesnt-match-the March 26, 2021 at 01:06PM