GitHub

Lab 2: Classification Using KNN and RNN Algorithms

Best when Data density is irregular Domain-meaningful distance threshold exists KNN is preferable when data density varies across the feature space, and when a fixed, predictable neighborhood is ...
GitHub

How/why is NumPy so much faster than KnnGraphTester/Lucene at exact brute-force KNN?

I haven't specifically done back to back testing, but just from watching NumPy do the brute-force "all pairs" exact NN dot-product to produce the visualization histograms, versus Lucene's exact NN, ...
Scientific Research Publishing

Performance of Different Machine Learning Algorithms for Credit Risk Classification ()

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
IEEE

Optimization Study of KNN Classification Algorithm on Large-Scale Datasets: Real-Time Optimization Strategy Based on Balanced KD Tree and Multi-threaded Parallel Computing

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 ...
IEEE

Classification of IRIS Dataset using Classification Based KNN Algorithm in Supervised Learning

Abstract: Machine learning is about prediction on unseen data or testing data and a set of algorithms are required to perform task on machine learning. There are three types of machine learning are ...