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I was trying to implement a model to distinguish between low or high pass filters acting on a white noise signal by using Scikit Learn's logistic regression. It seems to be working fine but when I extract the parameters `b=intercept_`

, and `m=coef_`

and use them to plot `1/(1+np.exp(-m*x-b)`

, the plot differs from when I use the predict function of the logistic regression. I can get it to be exactly by multiplying everything in `np.exp()`

by an arbitrarily large number but I am not sure what the exact value is. My aim was to use the `intercept_`

parameter as an estimate for the cut-off frequency that's why I need the exact value of the parameter, the other one is just for determining between high and low pass so all I need is the sign. Anyone by any chance know what it is? I looked everywhere but I still cannot seem to find the answer.

Thank you for your time.

This question was answered on the stats SE where I also posted it. https://stats.stackexchange.com/questions/335531/coefficients-from-logistic-regression-using-scikit-learn/335533#335533

– Jepsilon – 2018-03-20T22:11:20.607