Standard hybrid learners that use domain knowledge require stronger knowledge that is hard and expensive to acquire. However, weaker domain knowledge can benefit from prior knowle...
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
This book covers several topics such as Classification, Classical Statistical Methods, Modern Statistical Techniques, Machine Learning of Rules and Trees, Neural Networks
Methods ...
Semisupervised clustering algorithms partition a given data set using limited supervision from the user. The success of these algorithms depends on the type of supervision and also...
To predict the 100 missing values from a time series of 5000 data points, given for the IJCNN 2004 time series prediction competition, recurrent neural networks (RNNs) are trained...
Xindi Cai, Nian Zhang, Ganesh K. Venayagamoorthy, ...