AIMC Topic: Support Vector Machine

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Automated feature engineering improves prediction of protein-protein interactions.

Amino acids
Over the last decade, various machine learning (ML) and statistical approaches for protein-protein interaction (PPI) predictions have been developed to help annotating functional interactions among proteins, essential for our system-level understandi...

Multivariate classification of drug-naive obsessive-compulsive disorder patients and healthy controls by applying an SVM to resting-state functional MRI data.

BMC psychiatry
BACKGROUND: Previous resting-state functional magnetic resonance imaging (rs-fMRI) studies have revealed intrinsic regional activity alterations in obsessive-compulsive disorder (OCD), but those results were based on group analyses, which limits thei...

Computer Vision Classification of Barley Flour Based on Spatial Pyramid Partition Ensemble.

Sensors (Basel, Switzerland)
Imaging sensors are largely employed in the food processing industry for quality control. Flour from malting barley varieties is a valuable ingredient in the food industry, but its use is restricted due to quality aspects such as color variations and...

Detection of Skin Cancer Using SVM, Random Forest and kNN Classifiers.

Journal of medical systems
Most common and deadly type of cancer is Skin cancer. The destructive kind of cancers in skin is Melanoma as well as it can be identified at the initial stage and can be cured completely. For the diagnosis of melanoma, the identification of the melan...

Heuristic filter feature selection methods for medical datasets.

Genomics
Gene selection is the process of selecting the optimal feature subset in an arbitrary dataset. The significance of gene selection is in high dimensional datasets in which the number of samples and features are low and high respectively. The major goa...

Cancer classification and pathway discovery using non-negative matrix factorization.

Journal of biomedical informatics
OBJECTIVES: Extracting genetic information from a full range of sequencing data is important for understanding disease. We propose a novel method to effectively explore the landscape of genetic mutations and aggregate them to predict cancer type.

A Real-Time Arrhythmia Heartbeats Classification Algorithm Using Parallel Delta Modulations and Rotated Linear-Kernel Support Vector Machines.

IEEE transactions on bio-medical engineering
Real-time wearable electrocardiogram monitoring sensor is one of the best candidates in assisting cardiovascular disease diagnosis. In this paper, we present a novel real-time machine learning system for Arrhythmia classification. The system is based...

Detection of Moving Object in Dynamic Visual Sequences Based on Partial Least Squares Classifier.

Journal of medical systems
Detection of moving object from a visual sequence plays a vital role for the tracking of object. The main objective of this proposed work is to detect and classify the various video sequences with the help of different classification algorithms. The ...