To make ALS applicable to logistic regression, we introduce an auxiliary function derived from Pólya-Gamma augmentation, allowing logistic loss to be minimized as a weighted squared loss. We apply the ...

Wilner levied sanctions against Ellis George for using AI-generated research to write a court filing in the case and against K&L Gates for failing to fact-check the original brief, disclose the ...

One way to speed up your Python programs is to write modules in the Zig language and use them in your Python code. Here's how to get started.

Machine learning models analyze complex patterns within medical datasets, enabling precise prediction and classification of diseases like CHD [14]- [18]. This study explores the application of three ...

The purpose of this work is to investigate the effectiveness of DensNet and Logistic Regression in terms of accurately predicting the classification of footwear trends.In this study, there are two ...

You can create a release to package software, along with release notes and links to binary files, for other people to use. Learn more about releases in our docs ...

PriyankaTaug / Sentiment-Classification-using-Logistic-Regression-in-python Public Notifications Fork 0 Star Security ...

4 keys to writing modern Python Here’s what you need to know (and do) if you want to write Python like it’s 2025, not 2005. How to use uv, the super-fast Python package installer ...

Ultimately, we employed decision trees, logistic regression, and random forests to reach our objective. Of these, random forest yielded the highest accuracy of 96%, making them useful for obtaining ...