Discriminative Learning Approach Based on Flexible Mixture Model for Medical Data Categorization and Recognition

Discriminative Learning Approach Based on Flexible Mixture Model for Medical Data Categorization and Recognition

In this paper, we propose a novel hybrid discriminative learning approach based on shifted-scaled Dirichlet mixture model (SSDMM) and Support Vector Machines (SVMs) to address some challenging problems of medical data categorization and recognition. The main goal is to capture accurately the intrins...

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Bibliographic Details
Main Authors: Fahd Alharithi, Ahmed Almulihi, Sami Bourouis, Roobaea Alroobaea, Nizar Bouguila
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Sensors
Subjects:
shifted-scaled Dirichlet distribution
mixture model
SVM kernels
data categorization and recognition
medical image analysis
Online Access:https://www.mdpi.com/1424-8220/21/7/2450

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