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Adagrad Algorithm Explained and Implemented from Scratch in Python

Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning models. #Adagrad #Optimization #Python Trump administration looking to sell ...
IEEE

Investigation on PCA and LDA Feature Extraction Algorithms with KNN Classifier Targetting to Improve Diagnostic Accuracy into Detection of Breast Cancer Malignancy

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) ...
GitHub

SPL Quantitative Trading Practice Series：The KNN Trading Strategy

The trading strategy is like this: 1. Set “up or not” as the target (target). If the closing price is higher than that of the previous date, assign 1 as the target value, otherwise assign -1 to it. 2.
IEEE

Ingenious K Nearest Neighbor based Systematic prediction of Early Floods in Uncertain Weather Forecasts

Abstract: The purpose of this research is to create and evaluate a clever K Nearest Neighbor-based systematic prediction system against the Decision Tree Classifier method for early flood detection in ...
Scientific Research Publishing

Tang, Y., Chang, Y. and Li, K. (2023) Applications of K-Nearest Neighbor Algorithm in Intelligent Diagnosis of Wind Turbine Blades Damage. Renewable Energy, 212, 855-864.

ABSTRACT: To ensure the efficient operation and timely maintenance of wind turbines, thereby enhancing energy security, it is critical to monitor the operational status of wind turbines and promptly ...
GitHub

knearest-neighbor-algorithm

This project demonstrates how to implement the K-Nearest Neighbors (KNN) algorithm for classification on a customer dataset. The program iterates through different values of k (number of neighbors) ...