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# KhyatiMahendru/weight_update_Huber.py

Created June 3, 2019 17:29
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 def update_weights_Huber(m, b, X, Y, delta, learning_rate): m_deriv = 0 b_deriv = 0 N = len(X) for i in range(N): # derivative of quadratic for small values and of linear for large values if abs(Y[i] - m*X[i] - b) <= delta: m_deriv += -X[i] * (Y[i] - (m*X[i] + b)) b_deriv += - (Y[i] - (m*X[i] + b)) else: m_deriv += delta * X[i] * ((m*X[i] + b) - Y[i]) / abs((m*X[i] + b) - Y[i]) b_deriv += delta * ((m*X[i] + b) - Y[i]) / abs((m*X[i] + b) - Y[i]) # We subtract because the derivatives point in direction of steepest ascent m -= (m_deriv / float(N)) * learning_rate b -= (b_deriv / float(N)) * learning_rate return m, b

Dear KhyatiMahendru,

I hope this message finds you well.

I am interested in using your Huber code.

However, I have no idea about python.

It would be appreciated if you could convert this python code to R?

Kind Regards,
Jeza