Scientific Research Publishing

Boosting Algorithm: An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ()

An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
GitHub

Add a Linear Classifier for Patient-Level Modeling

We should add a linear classifier (logistic regression style) as an alternative to the current MLP in patient-level modeling. Same input format and preprocessing as MLP (patient feature vectors).
GitHub

A CNN is a kind of network architecture for deep learning algorithms and is specifically used for image recognition and tasks that involve the processing of pixel data. This ...

The Convolution Layer: Convolution is an orderly procedure where two sources of information are intertwined; it’s an operation that changes a function into something else. Convolutions have been used ...
Scientific Research Publishing

Comparing Classification Models for Predicting Malaria: A Case Study of Malaria Incidence in Kenya ()

1 Department of Mathematics, Meru University of Science & Technology (MUST), Meru, Kenya. 2 Department of Mathematics, Pan African University Institute of Basic Sciences Technology and Innovations ...
Nasdaq

MicroAlgo Inc. Announces a Quantum Entanglement-Based Novel Training Algorithm — Entanglement-Assisted Training Algorithm for Supervised Quantum Classifiers

This press release contains statements that may constitute "forward-looking statements." Forward-looking statements are subject to numerous conditions, many of which are beyond the control of ...
Seeking Alpha

MicroAlgo Inc. Develops Classifier Auto-Optimization Technology Based on Variational Quantum Algorithms, Accelerating the Advancement of Quantum Machine Learning

SHENZHEN, China, May 2, 2025 /PRNewswire/ -- MicroAlgo Inc. (MLGO) (the "Company" or "MicroAlgo") announced today the launch of their latest classifier auto-optimization technology based on ...
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) ...
IEEE

Dynamic Linear Classifier System for Hyperspectral Image Classification for Land Cover Mapping

Abstract: Exploitation of the spectral capabilities of modern hyperspectral image demands efficient preprocessing and analyses methods. Analysts’ choice of classifier and dimensionality reduction (DR) ...
Frontiers

EEG channel and feature investigation in binary and multiple motor imagery task predictions

Introduction: Motor Imagery (MI) Electroencephalography (EEG) signals are non-stationary and dynamic physiological signals which have low signal-to-noise ratio. Hence, it is difficult to achieve high ...