A modular text classification system that detects misinformation across multiple domains. Each niche has its own dataset, labeling rules, and baseline models (TF-IDF + Logistic Regression / Linear SVM ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Abstract: This paper presents a novel approach to binary classification using dynamic logistic ensemble models. The proposed method addresses the challenges posed by datasets containing inherent ...
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 ...
Background: Early neurological improvement (ENI) is a critical prognostic indicator for acute ischemic stroke (AIS) patients undergoing intravenous thrombolysis with recombinant tissue plasminogen ...
OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...
Abstract: The classification problem represents a funda-mental challenge in machine learning, with logistic regression serving as a traditional yet widely utilized method across various scientific ...
1 Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan 2 RIKEN Center for Advanced Intelligence Project, Tokyo, Japan In recent years, a learning method for classifiers using ...
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