SVM for FT‐MIR prostate cancer classification: An alternative to the traditional methods

LFS Siqueira, CLM Morais… - Journal of …, 2018‏ - Wiley Online Library
In this paper, principal component analysis (PCA), successive projections algorithm (SPA),
and genetic algorithm (GA) followed by support vector machines (SVM), combined with …

Vertical and horizontal DNA differential methylation analysis for predicting breast cancer

AF Al-Juniad, TS Qaid, MYH Al-Shamri… - IEEE …, 2018‏ - ieeexplore.ieee.org
DNA methylation plays an important role for initiation and development of human cancers;
therefore, it is used as a biological marker for early detection of cancer. A huge number of …

A new and fast correntropy-based method for system identification with exemplifications in low-SNR communications regime

AR Heravi, GA Hodtani - Neural Computing and Applications, 2019‏ - Springer
One of the most significant issues in machine learning is system identification with many
applications, eg, channel estimation (CE) in digital communications. Introducing a new …

[PDF][PDF] Polytomous Logistic Regression Based Random Forest Classifier for Diagnosing Cancer Disease

S Jeyasingh, M Veluchamy - Journal of Cancer Science and …, 2018‏ - researchgate.net
An early prediction of cancer disease is important for successful treatment. Recently, many
research works have been designed for classification of cancer diseases and early …

Comparación de algoritmos evolutivos para la optimización en la clasificación de la obesidad en escolares

ACA Rodríguez, CAT Naira, FMV Huyhua… - …, 2016‏ - revistaucmaule.ucm.cl
El estudio tiene por objetivo comparar tres tipos de algoritmos evolutivos diferentes: Real
Encoding Particle Swarm Optimization (REPSO–C), Incremental Learning with Genetic …

[PDF][PDF] A Comparative Analysis of Learning Techniques for Cancer Risk Prediction based on Medical Textual Records

C Fócil-Arias, G Sidorov, A Gelbukh… - Advances in …, 2016‏ - rcs.cic.ipn.mx
In this paper, we compare the performance of a variety of machine learning algorithms,
including supervised Naïve Bayes, J48, SVM, Random Tree, Random Forest, and non …