IEEE

Refining Sorghum Weed Classification with Dimension Reduction Techniques in Machine Learning

This paper explores the refinement of sorghum weed classification by applying dimension-reduction techniques in machine learning. Utilizing a comprehensive dataset of sorghum weed types, the study ...
Frontiers

BrainInsights: a comprehensive framework for pre-processing, analysis, and interpretation of neuroimaging data using traditional statistics and machine learning

Neuroimaging presents us with an in-depth understanding about brain structure and function, yet the data complexity poses significant analytical challenges. Current frameworks suffer from issues such ...
IEEE

Multispace Dimensionality Reduction Based on Extreme Learning Machine-Assisted Autoencoder for High-Dimensional Expensive Optimization

Abstract: Faced with high-dimensional expensive optimization problems (HEOPs), existing high-dimensional expensive optimization algorithms (HEOAs) struggle to locate promising areas quickly due to a ...
Janesville Gazette

New 'harm reduction' vending machine placed at SSM-Health St. Mary's

JANESVILLE — SSM Health St. Mary’s Hospital — Janesville and Rock County Public Health this week unveiled a new harm reduction vending machine for the community. “All vending machine supplies are ...
Nature

Robust evaluation of classical and quantum machine learning under noise, imbalance, feature reduction and explainability

Quantum machine learning (QML) has emerged as a promising paradigm for solving complex classification problems by leveraging the computational advantages of quantum systems. While most traditional ...
Frontiers

Estimating rice yield-related traits using machine learning models integrating hyperspectral and texture features

Rapidly estimating multiple trait indicators simultaneously, nondestructively, and with high precision is an important means of accurate diagnosis in modern phenomics. Increasing the accuracy of ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
LinkedIn

Dimensionality Reduction in Machine Learning: PCA, t-SNE, and LDA Explained Simply

🧹 Remove noise & redundant features 🚀 Speed up model training 📊 Make data visualizable (2D/3D) 🧠 Improve generalization and performance 💡 Help unsupervised learning (like clustering) work better ...
Nature

Developing machine learning for heterogeneous catalysis with experimental and computational data

Machine learning techniques have emerged as a useful tool for identifying complex patterns and correlations in large datasets, such as associating catalyst performance to its physicochemical ...
GitHub

ML Algorithm Selector GUI

The ML Algorithm Selector is an interactive desktop application built with Python and Tkinter. It guides users through a decision-making process to identify suitable machine learning algorithms for ...
LinkedIn

Dimensionality Reduction in Machine Learning

Dimensionality reduction is a crucial preprocessing step in machine learning that involves reducing the number of input variables in a dataset while retaining its essential information. This process ...