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) ...
C&EN

Coal Air-Dry Basis Sulfur Content Detection Model Based on Hippopotamus Optimization Algorithm and Two Hidden Layer Extreme Learning Machine

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Coal is a solid combustible organic rock formed from the ...
Hosted on MSN

RMSProp Optimization from Scratch in Python

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks efficiently. #RMSProp #Optimization #DeepLearning Trump Cuts Millions After ...
GitHub

Data Structures and Algorithms Repository

Welcome to the Data Structures and Algorithms Repository! My aim for this project is to serve as a comprehensive collection of problems and solutions implemented in Python, aimed at mastering ...
Frontiers

A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention

Introduction: The motion of a ship at sea is complex. This motion is affected by environmental factors such as wind, waves, and currents. These factors cause the ship’s movement to be nonlinear, ...
IEEE

Comparison of PCA and LDA Dimensionality Reduction Algorithms based on Wine Dataset

Abstract: In the construction of machine learning model, when the input data dimension is too large and the data characteristics are particularly complex, the complexity of the model will increase, ...
Scientific Research Publishing

Lin, J. and He, J. (2022) Parallel Random Forest Prediction Algorithm Based on PCA Stratified Sampling in the Big Data Environment. China Management Informationization, 25, 172 ...

ABSTRACT: To improve the efficiency of air quality analysis and the accuracy of predictions, this paper proposes a composite method based on Vector Autoregressive (VAR) and Random Forest (RF) models.
Frontiers

Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models

Introduction: Parkinson’s disease (PD) heterogeneity poses challenges to the current development of discovering the best therapeutic targets. Conclusion: Our findings suggest that, while PD is ...