Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models by Benedictor Alexander Nguchu, Benedictor Alexander Nguchu, Yifei Han, Yanming Wang, Peter Shaw

“…The features were specifically the gray matter volume and dopaminergic features of the neostriatum, i.e., the caudate, putamen, and anterior putamen. We use machine learning (ML) algorithms, including Random Forest, Logistic Regression, and Support Vector Machine, to evaluate the diagnostic power of the brain features and network patterns in differentiating the PD subtypes and distinguishing PD from HC. …”
Get full text

Identification of soil texture and color using machine learning algorithms and satellite imagery by Jiyang Wang

Get full text

Appraising the Pile Settlement Rates by Support Vector Regression Optimized Using the Novel Optimization Algorithms by Argyros Maris

Subjects: Get full text

Optimasi Parameter Support Vector Machine Dengan Algoritma Genetika Untuk Analisis Sentimen Pada Media Sosial Instagram by I Putu Dedy Wira Darmawan, Gede Aditra Pradnyana, Ida Bagus Nyoman Pascima

Subjects: Get full text

Performance Evaluation of Some Selected Classification Algorithms in a Facial Recognition System by Michael Olumuyiwa Adio, Ogunmakinde Jimoh Ogunwuyi, Mayowa Oyedepo Oyediran, Adebimpe Omolayo Esan, Olufikayo Adepoju Adedapo

“…The three selected supervised learning classification algorithms: Learning Vector Quantization (LVQ), Relevance Vector Machine (RVM), and Support Vector Machine (SVM) performance were evaluated so as to know the most effective out of the selected algorithms for facial images classification. …”
Get full text

Sentiment Analysis using Support Vector Machine and Random Forest by Talha Ahmed Khan, Rehan Sadiq, Zeeshan Shahid, Muhammad Mansoor Alam, Mazliham Bin Mohd Su'ud

Get full text

Application of Support Vector Machines in High Power Device Technology by RAO Wei, LI Yong, YAN Ji

“…As a machine learning algorithm, support vector machine(SVM) has the advantages of good nonlinear processing ability, theoretical global optimum and overcoming the curse of dimensionality. …”
Get full text

A Novel Support Vector Machine with Globality-Locality Preserving by Cheng-Long Ma, Yu-Bo Yuan

“…Support vector machine (SVM) is regarded as a powerful method for pattern classification. …”
Get full text

A New Support Vector Machine Based on Convolution Product by Wei-Chang Yeh, Yunzhi Jiang, Shi-Yi Tan, Chih-Yen Yeh

“…The support vector machine (SVM) and deep learning (e.g., convolutional neural networks (CNNs)) are the two most famous algorithms in small and big data, respectively. …”
Get full text

Characterization of High-Speed Steels—Experimental Data and Their Evaluation Supported by Machine Learning Algorithms by Manfred Wiessner, Ernst Gamsjäger

“…By supervised learning via a support vector machine, hyperplanes are constructed that allow separating the clusters from each other based on the X-ray measurements. …”
Get full text

Artificial Intelligence and/or Machine Learning Algorithms in Microalgae Bioprocesses by Esra Imamoglu

Subjects: Get full text

Application of stochastic methods, wavelet transformations and support vectors for the study of electroencephalogram signals by Veronika V. Tolmanova, Denis A. Andrikov

Subjects: “…support vector method…”
Get full text

Detecting tropical freshly-opened swidden fields using a combined algorithm of continuous change detection and support vector machine by Ningsang Jiang, Peng Li, Zhiming Feng

“…However, the CCD-derived temporal attributes and other multi-dimension features are seldom utilized to monitor swidden agriculture. Here, a combined algorithm integrating CCD and Support Vector Machine (SVM) is firstly developed to comprehensively highlight fundamental characteristics of swidden agriculture for maximumly and effectively mapping freshly opened swiddens. …”
Get full text

Squirrel search algorithm-support vector machine: Assessing civil engineering budgeting course using an SSA-optimized SVM model by He Yanqing, Shi Ling, Yao Xiaoqin, Zhang Haojie, Al-Barakati Abdullah A.

Subjects: Get full text

Prediction Model For Students' On-Time Graduation Using Algorithm Support Vector Machine (SVM) Based  Particle Swarm Optimization (PSO) by Syarif Hidayatulloh, Gandung Triyono, Kiki Ari Suwandi kosasih

Get full text

Exploratory Study on Screening Chronic Renal Failure Based on Fourier Transform Infrared Spectroscopy and a Support Vector Machine Algorithm by Yushuai Yuan, Li Yang, Rui Gao, Cheng Chen, Min Li, Jun Tang, Xiaoyi Lv, Ziwei Yan

“…This study proposes a cost-effective and reliable method for detecting CRF based on Fourier transform infrared (FT-IR) spectroscopy and a support vector machine (SVM) algorithm. We measured and analyzed the FT-IR spectra of serum from 44 patients with CRF and 54 individuals with normal renal function. …”
Get full text

Comparison of K-Nearest Neighbor, Support Vector Machine, Random Forest, and C 4.5 Algorithms on Indoor Positioning System by M Rizky Astari, Muhammad Taufiq Nuruzzaman, Bambang Sugiantoro

Get full text

Implementation of the Support Vector Machine (SVM) Algorithm on Sentiment Analysis of Public Opinion on The Prohibition of the use of Syrupy Drugs for Kidney Health by Galih Purnomo, Rumini Rumini, Tri Susanto

“…This research concludes that the Support Vector Machine (SVM) algorithm with a linear kernel achieves the highest accuracy in sentiment analysis.…”
Get full text

Interpretable prognostic modeling for long-term survival of Type A aortic dissection patients using support vector machine algorithm by Hao Cai, Yue Shao, Xuan-yu Liu, Chang-ying Li, Hao-yu Ran, Hao-ming Shi, Cheng Zhang, Qing-chen Wu

“…Based on the advantages of the model and the characteristics of the data set, we subsequently developed a machine learning-based prognostic model using Support Vector Machine (SVM) and evaluated its performance across key metrics. …”
Get full text

Comparison of the Accuracy Between Naive Bayes Classifier and Support Vector Machine Algorithms for Sentiment Analysis in Mobile JKN Application Reviews by Erni Septiani, Tubagus M. Akhriza, Mochamad Husni

“…The large number of reviews of the Mobile JKN application on the Google Play Store requires sentiment analysis with an algorithm that produces the best accuracy. This research compares the accuracy obtained from the Naive Bayes Classifier (NBC) and Support Vector Machine (SVM) algorithms. …”
Get full text