Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for ...

Abstract: This work aims to compare two different Feature Extraction Algorithms (FEAs) viz. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), using a K-Nearest Neighbor (KNN .

This project aims to build a complete pattern recognition system to solve classification problems using the k-Nearest Neighbors (KNN) algorithm. To classify chest X-ray images into three categories: ...

The new KNN algorithm is applied in two experiments through python. The result shows that the efficiency of the new KNN algorithm is improved greatly under certain situations and its accuracy also has ...

First proposed by the US Air Force School of Aviation Medicine in 1951, and having to accommodate itself to the state-of-the-art of mid-20th century computing hardware, K-Nearest Neighbors (KNN) is a ...

For this introduction I am going to define key terms so we can do into more depth about the applications and uses of data structures and algorithms ... interpreter on how to classify the variable. In ...