Automatic detection of cognitive distortions from short written text could support large-scale mental-health screening and digital cognitive-behavioural therapy (CBT). Many recent approaches rely on ...

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...

🏥 AI-powered breast cancer classification using Logistic Regression with 95% accuracy. Features interactive Gradio web interface for real-time predictions on 30 diagnostic parameters from Wisconsin ...

Heart disease classification using machine learning algorithms with hyperparameter tuning for optimized model performance. Algorithms include XGBoost, Random Forest, Logistic Regression, and moreto ...

Abstract: In the field of document image processing and analysis, the task of document classification holds significant importance, where the goal is to automatically classify documents based on their ...