Frontiers

Flood susceptibility mapping in El Niño Phenomenom integrating multitemporal radar analysis, GIS and machine learning techniques, Piura river basin, Peru

Floods represent the most frequent natural hazard, generating significant impacts on people as well as considerable economic and environmental losses worldwide. These events are particularly ...
GitHub

Organize, prepare, classify using PCA, standardization, and normalization, and apply the appropriate machine learning method for the task

There was an error while loading. Please reload this page. In this assessment, we explore a dataset containing 4601 rows and 59 columns, aiming to uncover insights ...
Scientific Research Publishing

Malhi, A. and Gao, R.X. (2004) PCA-Based Feature Selection Scheme for Machine Defect Classification. IEEE Transactions on Instrumentation and Measurement, 53, 1517-1525.

ABSTRACT: One exciting area within computer vision is classifying human activities, which has diverse applications like medical informatics, human-computer interaction, surveillance, and task ...
Too Old to Operate

Predictive Utility of Diverse Machine Learning Models for PCa Local Recurrence Following RP

The following is a summary of “Practical Clinical Role of Machine Learning Models with Different Algorithms in Predicting Prostate Cancer Local Recurrence after Radical Prostatectomy,” published in ...
CU Boulder News & Events

Understanding Principal Component Analysis in PyTorch

PCA is an important tool for dimensionality reduction in data science and to compute grasp poses for robotic manipulation from point cloud data. PCA can also directly used within a larger machine ...
Scientific Research Publishing

Face Reconstruction Using Hybrid PCA, LDP and SVM Machine Learning ()

This paper aims to develop a platform that allows face features to be extracted faster using multiple algorithms for looking up people in a large database. We will be presenting an enhanced technique ...
IEEE

Using PCA Machine Learning Approach Based on Psychological Questionnaires and Spectral Characteristics of the EEG to Separate the Healthy Participants and Participants with ...

Abstract: Statistical method Principal Component Analysis (PCA) based on psychological questionnaires and EEG spectral characteristics was used to reduce the complex data by finding the most important ...