AIMC Topic: Support Vector Machine

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Using CatBoost algorithm to identify middle-aged and elderly depression, national health and nutrition examination survey 2011-2018.

Psychiatry research
Depression is one of the most common mental health problems in middle-aged and elderly people. The establishment of risk factor-based depression risk assessment model is conducive to early detection and early treatment of high-risk groups of depressi...

A Machine-Learning-Based System for Prediction of Cardiovascular and Chronic Respiratory Diseases.

Journal of healthcare engineering
Cardiovascular and chronic respiratory diseases are global threats to public health and cause approximately 19 million deaths worldwide annually. This high mortality rate can be reduced with the use of technological advancements in medical science th...

Target Recognition of SAR Images Based on SVM and KSRC.

Computational intelligence and neuroscience
A synthetic aperture radar (SAR) target recognition method combining linear and nonlinear feature extraction and classifiers is proposed. The principal component analysis (PCA) and kernel PCA (KPCA) are used to extract feature vectors of the original...

Classification of electrocardiogram signals with waveform morphological analysis and support vector machines.

Medical & biological engineering & computing
Electrocardiogram (ECG) indicates the occurrence of various cardiac diseases, and the accurate classification of ECG signals is important for the automatic diagnosis of arrhythmia. This paper presents a novel classification method based on multiple f...

Identifying N7-methylguanosine sites by integrating multiple features.

Biopolymers
Recent studies reported that N7-methylguanosine (m7G) plays a vital role in gene expression regulation. As a consequence, determining the distribution of m7G is a crucial step towards further understanding its biological functions. Although biologica...

Support Vector Machine Classifiers Show High Generalizability in Automatic Fall Detection in Older Adults.

Sensors (Basel, Switzerland)
Falls are a major cause of morbidity and mortality in neurological disorders. Technical means of detecting falls are of high interest as they enable rapid notification of caregivers and emergency services. Such approaches must reliably differentiate ...

Performing sequential forward selection and variational autoencoder techniques in soil classification based on laser-induced breakdown spectroscopy.

Analytical methods : advancing methods and applications
The feasibility and accuracy of several combination classification models, , quadratic discriminant analysis (QDA), random forest (RF), Bernoulli naïve Bayes (BNB), and support vector machine (SVM) classification models combined with either sequentia...

Study on 3D Image Reconstruction Model of Sparring Action Based on Graph Neural Network (GNN).

Computational intelligence and neuroscience
With the advent of the information age, human demand for information is increasing day by day. The emergence of the concept of big data has triggered a new round of technological revolution, and visual information plays an important role in informati...

Tracking strategy changes using machine learning classifiers.

Behavior research methods
In complex tasks, high performers often have better strategies than low performers, even with similar amounts of practice. Relatively little research has examined how people form and change strategies in tasks that permit a large set of strategies. O...