Results 61 to 70 of about 8,989,075 (297)
International Journal of Distributed Sensor Networks, 2017 This article comparatively analyzed the performance of K-nearest neighbor, support vector machine, and artificial neural network classifiers for driver drowsiness detection with different road geometries (straight segments and curve segments) based on a ...
Zhenlong Li +2 more
doaj +1 more source
Support Vector Machine as Tool for Classifying Coffee Beverages
, 2020 Classifiers are tools widely used nowadays to process data and obtain prediction models that are trained through supervised learning techniques; there is a wide variety of sensors that acquire the data to be processed, such as the voltammetric electronic tongue, as a device employed to analyze food compounds.
José Varela Aldás +5 more
openaire +2 more sources
Advanced Engineering Materials, EarlyView.Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source
A Differential Privacy Support Vector Machine Classifier Based on Dual Variable Perturbation
IEEE Access, 2019 Data mining technology can be used to dig out potential and valuable information from massive data, and support vector machine (SVM) is one of the most widely used and most efficient methods in the field of data mining classification.
Yaling Zhang +2 more
doaj +1 more source
Effective Handling of Missing Values in Datasets for Classification Using Machine Learning Methods
Information, 2023 The existence of missing values reduces the amount of knowledge learned by the machine learning models in the training stage thus affecting the classification accuracy negatively. To address this challenge, we introduce the use of Support Vector Machine (
Ashokkumar Palanivinayagam +1 more
doaj +1 more source
Decision Boundaries and Classification Performance Of SVM And KNN Classifiers For 2-Dimensional Dataset [PDF]
, 2009 Support Vector Machines (SVM) and K-Nearest Neighborhood (k-NN) are two most popular classifiers in machine learning. In this paper, we intend to study the generalization performance of the two classifiers by visualizing the decision boundary of each ...
Hussain, Aini
core
New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design
Advanced Engineering Materials, EarlyView.This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare +5 more
wiley +1 more source
AN IMPLEMENTATION OF EIS-SVM CLASSIFIER USING RESEARCH ARTICLES FOR TEXT CLASSIFICATION [PDF]
ICTACT Journal on Soft Computing, 2016 Automatic text classification is a prominent research topic in text mining. The text pre-processing is a major role in text classifier. The efficiency of pre-processing techniques is increasing the performance of text classifier.
B Ramesh, J G R Sathiaseelan
doaj
Biomedicines, 2020 Background: The challenge of differentiating, at an early stage, Parkinson’s disease from parkinsonism caused by other disorders remains unsolved. We proposed using an artificial neural network (ANN) to process images of dopamine transporter single ...
Chung-Yao Chien +4 more
doaj +1 more source