marktechpost

Kernel Principal Component Analysis (PCA): Explained with an Example

Dimensionality reduction techniques like PCA work wonderfully when datasets are linearly separable—but they break down the moment nonlinear patterns appear. That’s exactly what happens with datasets ...
Scientific Research Publishing

Comparative Research in Sentiment Analysis Using Machine Learning Technique ()

In today’s digital background, sentiment analysis has become an essential factor of Natural Language Processing (NLP), offering valuable insights from vast online data sources. This paper presents a ...
The Daily Northwestern

Q&A: Outgoing ETHS principal discusses social emotional learning, strengthening school community

Taya Kinzie, the outgoing principal of Evanston Township High School and assistant superintendent of ETHS District 202, said she has always bled blue and orange. Her children, sisters, mother, ...
C&EN

Automated Machine-Learning-Driven Analysis of Microplastics by TGA-FTIR for Enhanced Identification and Quantification

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Microplastics persist as ubiquitous environmental contaminants, and efficient methods ...
Frontiers

Integrating machine learning and multi-omics analysis to reveal nucleotide metabolism-related immune genes and their functional validation in ischemic stroke

Background: Ischemic stroke (IS) is a major global cause of death and disability, linked to nucleotide metabolism imbalances. This study aimed to identify nucleotide metabolism-related genes ...
C&EN

Open-Source Visual Programming Software for Introducing Principal Component Analysis to the Analytical Curriculum

Principal component analysis (PCA) is one of the most common exploratory data analysis techniques with applications in outlier detection, dimensionality reduction, graphical clustering, and ...
Science Daily

'Democratizing chemical analysis':Chemists use machine learning and robotics to identify chemical compositions from images

Chemists have created a machine learning tool that can identify the chemical composition of dried salt solutions from an image with 99% accuracy. By using robotics to prepare thousands of samples and ...
IEEE

Advancing Smart Grid Stability Through Machine Learning and Principal Component Analysis

Abstract: Innovative solutions are required to maintain the stability, efficiency, and dependability of modern smart grid systems due to their increasing complexity and demand. This paper explores the ...
Frontiers

Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia

Jiangxi Province Key Laboratory of Immunology and Inflammation, Jiangxi Provincial Clinical Research Center for Laboratory Medicine, Department of Clinical Laboratory, The Second Affiliated Hospital, ...
IEEE

A Method of Kernel Principal Component Analysis and Machine Learning Algorithms for Fault Diagnosis of Power Transformers

Abstract: As one of the most important equipment in the power system, it is of great significance to conduct fault diagnosis research on transformers. Aiming at the problem of difficult selection of ...