A faster SVM classification technique for remote sensing images using reduced training samples
The support vector machine (SVM) has been used as an efficient tool in data mining tasks
during the last 2 decades. It is also used for supervised classification with reasonable …
during the last 2 decades. It is also used for supervised classification with reasonable …
An overview of diabetes mellitus prediction through machine learning approaches
Diabetes, typically stated by medical professionals as DM (Diabetes Mellitus), explains a
collection of metabolic illnesses during which the patient has high glucose, either as a result …
collection of metabolic illnesses during which the patient has high glucose, either as a result …
Using neural networks and SVMs for automatic medical diagnosis: a comprehensive review
D Vassis, BA Kampouraki, P Belsis… - … IC-ININFO 2014), 2015 - ui.adsabs.harvard.edu
In this paper we make a comprehensive review regarding the use of neural networks in
automated medical diagnosis, with a special emphasis in Support Vector Machines (SVMs) …
automated medical diagnosis, with a special emphasis in Support Vector Machines (SVMs) …
[PDF][PDF] Design of classifier for detection of diabetes using neural network and fuzzy k-nearest neighbor algorithm
M Pradhan, K Kohale, P Naikade… - International Journal …, 2012 - researchgate.net
Diabetes Mellitus is one of the growing vitally fatal diseases world-wide. A design of
classifier for the detection of Diabetes Mellitus with optimal cost and precise performance is …
classifier for the detection of Diabetes Mellitus with optimal cost and precise performance is …
[PDF][PDF] Critical analysis of data mining techniques on medical data
The use of Data mining techniques on medical data is dramatically soar for determining
helpful things which are used in decision making and identification. The most extensive data …
helpful things which are used in decision making and identification. The most extensive data …
Application of real-valued negative selection algorithm to improve medical diagnosis
Disease-causing organisms have shown to be adaptive in nature, and for a proper disease
diagnosis, the need for disease detection system becomes paramount. Varieties of different …
diagnosis, the need for disease detection system becomes paramount. Varieties of different …
[PDF][PDF] Diabetes prediction by supervised and unsupervised learning with feature selection
E Rabina, C Anshu - International Journal of Advanced Research, 2016 - Citeseer
Two approaches to building models for prediction of the onset of Type diabetes mellitus in
juvenile subjects were examined. A set of tests performed immediately before diagnosis was …
juvenile subjects were examined. A set of tests performed immediately before diagnosis was …
[PDF][PDF] An alternative algorithm for classification large categorical dataset: k-mode clustering reduced support vector machine
SW Purnami, JM Zain, T Heriawan - International Journal of …, 2011 - academia.edu
The reduced support vector machine (RSVM) is extension method of smooth support vector
machine (SSVM) for handling computational difficulties as well as reduces the model …
machine (SSVM) for handling computational difficulties as well as reduces the model …
[PDF][PDF] Diabetes Prediction Using Machine Learning Algorithms
R Bothra - International Journal of Engineering Applied Sciences …, 2021 - researchgate.net
Diabetes mellitus is a disease in which blood sugars level is abnormally high due to inability
of the body to produce or respond normally to insulin. It is among the critical disease and lots …
of the body to produce or respond normally to insulin. It is among the critical disease and lots …
A convolutional neural network based feature extractor with discriminant feature score for effective medical image classification
R Banupriya, AR Kannan - NeuroQuantology, 2020 - search.proquest.com
Abstract In Computer-Aided Diagnosis (CAD) systems, major role is played by classification
of medical images. Conventional methods uses texture features, color and shape …
of medical images. Conventional methods uses texture features, color and shape …