49 – Logistic Regression using scikit-learn in Python




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This tutorial explains the few lines to code logistic regression in Python using scikit-learn library.

The code from this video is available at: https://github.com/bnsreenu/python_for_microscopists

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Comment List

  • DigitalSreeni
    January 9, 2021

    The result of Logistic Regression function is a real number within [0,1]. Thus, you can set df.Productivity within [0,1].
    However, you set df.Productivty=2 in Line 25. It must be 0. Do I miss something?

  • DigitalSreeni
    January 9, 2021

    Nice tutorial. However, instead you telling us go the previous tutorial, why not leave the link here, so it would be easy to find it. Or better still leave a link to the play list

  • DigitalSreeni
    January 9, 2021

    Can we do this method for multiple class classification problems? instead of 2

  • DigitalSreeni
    January 9, 2021

    what if the output is not only "bad" or "good" but what if there's "normal" too? It isn't binary anymore. How can i deal with it please?

  • DigitalSreeni
    January 9, 2021

    Thanks for your nice work. May you show me what difference between random_state =20 or 1 or other numbers that are not None? Thanks

  • DigitalSreeni
    January 9, 2021

    Thank YOU for your time and patience for the videos!

  • DigitalSreeni
    January 9, 2021

    I think you can improve the prediction keeping user feature un the model using one hot encoding,

  • DigitalSreeni
    January 9, 2021

    Great job man. i know about logistic regretion but not using model selection and train test imports.. Good to learn a quick way to make it
    Some improvements on this code, find a way to show the sigmoid and the cost x iteraction graph.
    edit: This code uses 100 iteractions as max number, wheres only 27 were needed. The Learning ratio or alpha, well i was looking for it, until realize that this is a Stochastic Average Gradient. Wich we can obtain the number, but we can't modify it..

  • DigitalSreeni
    January 9, 2021

    Great work best video for machine learning algorithm I've ever seen

  • DigitalSreeni
    January 9, 2021

    Nice step by step explanation 🙂

  • DigitalSreeni
    January 9, 2021

    Sreeni……exceptional work man! The quality of your content and simplicity in explaining key concepts is very impressive. Keep up the awesome work!

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