Cai Cai's Machine Learning Sklearn Class: Understandable from Scratch, from Model Invocation to Practical Implementation

The design of sklearn follows the "Swiss Army Knife" principle, integrating six core modules: Data Preprocessing: Similar to ...
IEEE

Non-Intrusive Load Monitoring Modeling and Analysis Based on Optimized K-Nearest Neighbor Algorithm

Abstract: Aiming at the problem that the recognition rate of the K-Nearest Neighbor (KNN) algorithm is not high in the face of similar power fingerprints in non-intrusive load recognition, an improved ...
GitHub

Python Maze Solver using A* Algorithm with Movement Constraints

A Python script with an AI algorithm that solves a 2D maze using the A* search algorithm - but, with specific movement constraints, to really force the AI earn its way out of the maze. This time, ...
Frontiers

Density peak clustering algorithm based on weighted mutual K-nearest neighbors

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) ...
GitHub

LLM4AD: Large Language Model for Algorithm Design

LLM4AD is an open-source Python-based Platform leveraging Large Language Models (LLMs) for Automatic Algorithm Design (AD). Please refer to the paper [LLM4AD] for detailed information, including the ...
IEEE

Enhancing Customer Retention: A Comprehensive Analysis of Churn Prediction with KNN

Abstract: Customer churn prediction is important for companies that want to keep their customers. The research paper shows how well the K-Nearest Neighbors (KNN) algorithm can predict when customers ...