I’m testing different examples of solving linear regression using sklearn, but it gives me wrong model. I have input feature x equals [1 2 3 4 5 6 7]. The output y is [14 39 74 119 174 239 314]. Correct result model should be f(x) = 5x^2 + 10x - 1. So, I add the second feature x^2. If I don’t use…

Hi @matrix , it is great you are trying out sklearn!! And please also try this: SGDRegressor(max_iter=500000, alpha=0, learning_rate='constant', eta0 = 0.0001, tol=1e-10, n_iter_no_change=2*len(X)) and I get Calculated model parameters w: [5.00017774 9.99841084], b: [-0.99708895] My config is no…

Solving linear regression with sklearn gives me wrong result

Course Q&A Machine Learning Specialization Supervised ML: Regression and Classification

rmwkwok July 19, 2022, 1:05am 4

You are welcome @matrix. I have two pieces of hints.

This can help justify my eta0.

n_iter_no_change has to do with the fact that you are using SGD, so each iteration considers only one sample of your dataset.

Cheers,
Raymond

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Solving linear regression with sklearn gives me wrong result

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