Search results for "Minimal Learning Machine"

showing 3 items of 13 documents

Orientation Adaptive Minimal Learning Machine for Directions of Atomic Forces

2021

Machine learning (ML) force fields are one of the most common applications of ML in nanoscience. However, commonly these methods are trained on potential energies of atomic systems and force vectors are omitted. Here we present a ML framework, which tackles the greatest difficulty on using forces in ML: accurate prediction of force direction. We use the idea of Minimal Learning Machine to device a method which can adapt to the orientation of an atomic environment to estimate the directions of force vectors. The method was tested with linear alkane molecules. peerReviewed

atomsComputer sciencebusiness.industryforce directionsmolekyylitOrientation (graph theory)nanotieteetatomitmachine learningkoneoppiminenMinimal learning machineComputer visionmoleculesArtificial intelligencebusiness
researchProduct

Minimal learning machine in hyperspectral imaging classification

2020

A hyperspectral (HS) image is typically a stack of frames, where each frame represents the intensity of a different wavelength of light. Each spatial pixel has a spectrum. In the classification of the HS image, each spectrum is classified pixel-by-pixel. In some of the real-time applications, the amount of the HS image data causes performance challenges. Those issues relate to the platforms (e.g. drones) payload restrictions, the issues of the available energy and to the complexity of the machine learning models. In this study, we introduce the minimal learning machine (MLM) as a computationally cheap training and classification machine learning method for the hyperspectral imaging classificatio…

Principal Component AnalysisMinimal Learning MachineArtificial neural networkPixelComputer sciencebusiness.industryFrame (networking)Payload (computing)spektrikuvausHyperspectral imagingPattern recognitionHyperspectral ImagingClassificationRandom forestSupport vector machineData pointkoneoppiminenkuvantaminenDistance LearningArtificial intelligencebusiness
researchProduct

Improvements and applications of the elements of prototype-based clustering

2018

Clustering or cluster analysis is an essential part of data mining, machine learning, and pattern recognition. The most popularly applied clustering methods are partitioning-based or prototype-based methods. Prototype-based clustering methods usually have easy implementability and good scalability. These methods, such as K-means clustering, have been used for different applications in various fields. On the other hand, prototype-based clustering methods are typically sensitive to initialization, and the selection of the number of clusters for knowledge discovery purposes is not straightforward. In the era of big data, in high-velocity, ever-growing datasets, which can also be erroneous, outl…

random projectionparallel computingknowledge discoveryclustering initializationminimal learning machinedata miningprototype-based clusteringmachine learningkoneoppiminenbig datarinnakkaiskäsittelyklusterianalyysitiedonlouhintarobust clusteringK-means
researchProduct