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Investigated how multi-class logistic regression would perform if the activation function was changed from softmax to sigmoid. It included mathematical analysis and empirical evaluation, such as rewriting the model from scratch. Tech: Python (scikit-learn, pandas)

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SaniyaAbushakimova/A-Study-of-Sigmoid-based-Multi-class-Logistic-Regression

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Project completed on Dec 9, 2021.

Purpose

  • Investigate how sigmoid-based multi-class logistic regression would perform compared to softmax_based one.

Content

  • Final Project/Final_project_report.pdf - Report (AAAI format) that contains description and results of the work done.
  • Final Project/Final_project_solution.ipynb - Jupyther Notebook with Data exploration, training procedures and experiments.
  • Final Project/Preprocessing.ipynb - Jupyter Notebook with data preprocessing.

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Investigated how multi-class logistic regression would perform if the activation function was changed from softmax to sigmoid. It included mathematical analysis and empirical evaluation, such as rewriting the model from scratch. Tech: Python (scikit-learn, pandas)

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