If it feels like social platforms suddenly “get” you more than they used to, you’re not imagining it! In 2026, feeds aren’t only reacting to what you click anymore. They’re predicting what you ...

To understand and implement the K-Nearest Neighbors (KNN) algorithm for solving classification problems using the Iris dataset. This project demonstrates data preprocessing, model training, evaluation ...

Abstract: The K-Nearest Neighbors (KNN) algorithm is a classical supervised learning method widely used in classification and regression problems. However, the KNN algorithm faces serious challenges ...

Hi, thanks for sharing your great work! I have a concern about the KNN in SCAN training. In the Eq.2 of your paper, you calculate the loss by maximizing the similarities between each anchor and its ...

Abstract: With the rapid development of information technology, the concept of big data is used in information collection on different things, especially for the text classification. This paper ...