Logistic_Regression

  1. Is there any derivation for the log loss function (from where did
    this function came)?

  2. How does gradient descent work in logistic regression?
    Like in linear regression our y was (y = b0 + b1x) and what we did
    there was randomly select a value for b1 and then kept updating it
    until we get a minimum MSE or the global minima.
    Here, in Logistic regression, our (y = sigmoid function), just wanted
    to know how gradient descent will work here? In linear regression we
    used a random value for b1, what will be that random value in logistic
    regression?

  3. After reading tons of articles I also got to know that logistic
    regression uses MLE(Maximum likelihood estimation). I couldn’t figure
    out where exactly we use MLE in this algorithm

© Copyright 2013-2021 Analytics Vidhya