In this paper, we proposed a framework, called Mulr4FL, for fault localization using a multivariate logistic regression model that combined both static and dynamic features collected from the program ...

Finally, multiple feature sets are combined and fed into a zero order optimization model, after which logistic regression is utilized to recognize each action. The proposed system has been evaluated ...

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 ...

Royalty-free licenses let you pay once to use copyrighted images and video clips in personal and commercial projects on an ongoing basis without requiring additional payments each time you use that ...

1️⃣ Logistic Regression – For yes/no questions (e.g., Will they click?) 2️⃣ Linear Regression – For predicting numbers (e.g., Price, score) 3️⃣ Decision Tree – Like a flowchart ...

Implementing binary / multiple logistic regression models, for the well known mnist dataset while also creating the support vector machine(SVM) models ...

Analysis of 2023 BRFSS data exploring the relationship between insurance status, flu shot uptake, and preventive care access. Includes data cleaning, EDA, logistic regression, and visualizations using ...