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    Home»Machine Learning»Classification using Logistic Regression in Python | by Dr. Soumen Atta, Ph.D. | Jan, 2025
    Machine Learning

    Classification using Logistic Regression in Python | by Dr. Soumen Atta, Ph.D. | Jan, 2025

    Team_AIBS NewsBy Team_AIBS NewsJanuary 13, 2025No Comments1 Min Read
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    Classification using Logistic Regression in Python

    Logistic Regression is a robust statistical technique used for binary and multi-class classification duties. Regardless of its identify, it’s a classification algorithm, not a regression algorithm. This weblog supplies a complete overview of logistic regression, its working mechanism, and its implementation in Python.

    Logistic Regression is a supervised studying algorithm used to foretell the chance of a goal variable belonging to a selected class. It estimates the chance utilizing the logistic operate (sigmoid operate) and maps the predictions to discrete lessons utilizing a threshold (generally 0.5 for binary classification).

    Logistic Function (Sigmoid Function)

    The operate outputs values within the vary (0, 1), which characterize chances.

    1. Binary Classification: Logistic regression predicts certainly one of two lessons (e.g., 0 or 1).
    2. Determination Boundary: A threshold (e.g., 0.5) is utilized to categorise information factors.
    3. Loss Operate: The optimization of logistic regression is completed utilizing the log-loss (cross-entropy)…



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