Robust predictive model for evaluating breast cancer survivability

K Park, A Ali, D Kim, Y An, M Kim, H Shin - Engineering Applications of …, 2013 - Elsevier
Objective Many machine learning models have aided medical specialists in diagnosis and
prognosis for breast cancer. Accuracy has been regarded as a primary measurement for the …

Breast cancer survivability prediction using labeled, unlabeled, and pseudo-labeled patient data

J Kim, H Shin - Journal of the American Medical Informatics …, 2013 - academic.oup.com
Background Prognostic studies of breast cancer survivability have been aided by machine
learning algorithms, which can predict the survival of a particular patient based on historical …

Prediction of movement direction in crude oil prices based on semi-supervised learning

H Shin, T Hou, K Park, CK Park, S Choi - Decision Support Systems, 2013 - Elsevier
Oil price prediction has long been an important determinant in the management of most
sectors of industry across the world, and has therefore consistently required detailed …

Stock price prediction based on a complex interrelation network of economic factors

K Park, H Shin - Engineering Applications of Artificial Intelligence, 2013 - Elsevier
Stock price prediction is a field that has been continuously interesting. Stock prices are
influenced by many factors such as oil prices, exchange rates, money interest rates, stock …

Bioinformatics: Trends in gene expression analysis

SA Raut, SR Sathe, A Raut - 2010 International Conference on …, 2010 - ieeexplore.ieee.org
Bioinformatics is an interesting combination of biology and computational sciences, which
help scientists and researchers to do more biological experiments to improve the life of living …

Active learning using Fuzzy-Rough Nearest Neighbor classifier for cancer prediction from microarray gene expression data

A Kumar, A Halder - International Journal of Pattern Recognition and …, 2020 - World Scientific
Cancer prediction from gene expression data is a very challenging area of research in the
field of computational biology and bioinformatics. Conventional classifiers are often unable …

Electricity price prediction based on semi-supervised learning and neural network algorithms

HS Kim, HJ Shin - Journal of Korean Institute of Industrial …, 2013 - koreascience.kr
Predicting monthly electricity price has been a significant factor of decision-making for plant
resource management, fuel purchase plan, plans to plant, operating plan budget, and so on …

基于两阶段学习的半监督支持向量机分类算法

陶新民, 曹盼东, 宋少宇, 付丹丹 - 信息与控制, 2012 - xk.sia.cn
提出了一种基于两阶段学习的半监督支持向量机(semi-supervised SVM) 分类算法.
首先使用基于图的标签传递算法给未标识样本赋予初始伪标识, 并利用k 近邻图将可能的噪声 …

[图书][B] Algorithms for training large-scale linear programming support vector regression and classification

PR Perea - 2011 - search.proquest.com
The main contribution of this dissertation is the development of a method to train a Support
Vector Regression (SVR) model for the large-scale case where the number of training …

Uni-class pattern-based classification model

MA Salama, AE Hassanien… - 2010 10th International …, 2010 - ieeexplore.ieee.org
This paper presents a model of a supervised machine learning approach for classification of
a dataset. The model extracts a set of patterns common in a single class from the training …