Learn how to implement the K-Nearest Neighbors (KNN) algorithm from scratch in Python! This tutorial covers the theory, coding process, and practical examples to help you understand how KNN works ...

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 ...

Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

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1 School of Computer Science and Technology, Yibin University, Yibin, China 2 School of Computer and Software, Southwest Petroleum University, Chengdu, China Ever since Density Peak Clustering (DPC) ...

Functions are the building blocks of Python programming. They let you organize your code, reduce repetition, and make your programs more readable and reusable. Whether you’re writing small scripts or ...

Embedding-based search outperforms traditional keyword-based methods across various domains by capturing semantic similarity using dense vector representations and approximate nearest neighbor (ANN) ...

1 Yibin University, School of Computer Science and Technology, Yibin, China 2 Southwest Petroleum University, School of Computer and Software, Chengdu, China Network security is the core guarantee for ...

Impact Statement: The adaptive k-Nearest Neighbor (AKNN) algorithm is an improvement over the traditional k-Nearest Neighbor (KNN) technique in machine learning. AKNN can assign a more appropriate ...

Abstract: Optimizing the K value in the K-Nearest Neighbor (KNN) algorithm is a critical step in enhancing model performance, particularly for tasks related to classification and prediction. The Elbow ...