Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

A modern, interactive web application for training and using Naive Bayes classifiers with beautiful visualizations. . ├── app.py # Flask application ├── model.py # Naive Bayes implementation ├── ...

1 Department of Computer Science, Rochester Institute of Technology, Rochester, USA. 2 Department of Computer Science, Rutgers University, New Brunswick, USA. Language identification is a fundamental ...

In an era of rapidly growing multimedia data, the need for robust and efficient classification systems has become critical, specifically the identification of class names and poses or styles. This ...

A suite of ML models—Logistic Regression, Random Forest, KNN, SVM, Gaussian Naive Bayes—was used to predict patient readmission. (1) Rasoul Samani, School of Electrical and Computer Engineering, ...

ABSTRACT: Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral ...

The goal of a machine learning regression problem is to predict a single numeric value. There are roughly a dozen different regression techniques such as basic linear regression, k-nearest neighbors ...

A Machine Learning based system to detect semantics in the form of semantic label and suggest optimized alternatives for Python and C++ function-based code snippet.Semantic Detection is language ...

Abstract: This paper investigates the impact of the probability distribution of a Naive Bayes classifier and the statistical distribution of the underlying feature data on the classifier's performance ...