A Husqvarna researcher developed a fast, interpretable PV hotspot-detection method using IR thermography and Lab* color-space features instead of heavy neural networks, achieving up to 95.2% accuracy ...

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

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Naive Bayes classifiers (GaussianNB, MultinomialNB, BernoulliNB, ComplementNB, CategoricalNB) currently do not support the class_weight parameter, while almost all other scikit-learn classifiers do.

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, ...

Service-based organizations may handle thousands of customer emails daily, placing a significant burden on IT help desks, customer service organizations, and other departments involved in reading, ...

Abstract: The purpose of this publication is to compare the accuracy of a new algorithm based on the Naive Bayesian classifier using the Laplace distribution and named the Laplace Naive Bayes ...

Abstract: This paper presents a naive Bayesian recognition and classification method based on extended Kalman filter, designed for multi-target tracking scenarios using multiple radars. The approach ...

ABSTRACT: In real-world applications, datasets frequently contain outliers, which can hinder the generalization ability of machine learning models. Bayesian classifiers, a popular supervised learning ...