New framework renders AI more trustworthy for cancer subtyping

Medical artificial intelligence (AI) faces a fundamental challenge: uncertainty quantification. Artificial neural networks ...
Scientific Research Publishing

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features ()

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...
IEEE

Improvement of KNN Algorithm and Research on Fruit Image Classification Technology

Abstract: The traditional K-Nearest Neighbor (KNN) algorithm often encounters problems such as weak feature expression ability and poor adaptability to fixed K-values in image classification tasks, ...
Scientific Research Publishing

Cover, T. and Hart, P. (1967) Nearest Neighbor Pattern Classification. IEEE Transactions on Information Theory, 13, 21-27.

ABSTRACT: Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for millions of deaths each year according to the World Health Organization (WHO). Early detection of ...
The New York Times

How A.I. Can Use Your Personal Data to Hurt Your Neighbor

Dr. Kasy is the author of the book “The Means of Prediction: How AI Really Works (and Who Benefits).” See more of our coverage in your search results.Encuentra más de nuestra cobertura en los ...
Wired

A New Algorithm Makes It Faster to Find the Shortest Paths

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...
Nature

‌Rockburst intensity grading prediction based on the LOF-ENN-KNN model‌

Rockburst is a typical dynamic disaster in deep underground engineering, and its accurate prediction is of great significance to ensure the safety of engineering. Aiming at the key problems in ...
Nature

Motor imagery EEG signal classification using novel deep learning algorithm

Electroencephalography (EEG) is widely used for neurological analysis, cognitive state monitoring, and disease diagnosis. Efficient classification of EEG signals is essential for detecting mental ...
LinkedIn

Introduction to KNN: The Lazy Yet Powerful Algorithm

The K-Nearest Neighbors (KNN) algorithm is one of the simplest yet highly effective machine learning techniques for classification and regression. Its intuitive approach—basing predictions on the ...
LinkedIn

K-Nearest Neighbors (KNN) Algorithm for Classification: Real-world Applications and Examples

K-Nearest Neighbors (KNN) is a simple yet effective supervised machine learning algorithm used for both regression and classification tasks. The algorithm works by finding the K nearest data points in ...
IEEE

An Improved Weighted KNN Algorithm About Text Classification Based on Spark Framework

Abstract: K-nearest neighbor classification algorithm can quickly deal with the classification problem in this paper, but when calculating the similarity, it will assign the same weight to all ...