Contact
How to shop
Delivery
Shopping guide
Feature Selection and Binary Classification Using Microarray Data
Background, Methods, and Comparison of Classifiers Using Univariate and Genetic Algorithm-Based Feature Selection and Supervised Learning Techniques
English
203 b
Delivery to Austria
30-day return policy
Customers also purchased
/
Paperback
34.39
€
/
Paperback
7.09
€
DNA microarray technology has greatly influenced the realms of biomedical research, with the hopes of significantly impacting the diagnosis and treatment of diseases. Microarrays have the ability to measure the expression levels of thousands of genes simultaneously. This research entails a rigorous and systematic comparison of statistical classifiers composed of supervised learning methods and either univariate or genetic algorithm-based multivariate feature subset selection (FSS) techniques, all applied to six published two-class microarray datasets. §These analyses should provide insights into univariate vs. multivariate FSS and how to obtain realistic and honest misclassification error rates via cross-validation (CV). Ultimately, this research puts to test the more traditional implementations of CV and FSS and provides a solid foundation on which these topics can and should be further investigated when performing limited-sample classification using high-dimensional gene expression data. §The analyses presented should be especially useful to researchers in the fields of bioinformatics, supervised learning, and variable selection, as well as anyone interested in microarray analysis.
About the book
English
Categories
Give this book today
It's easy
1 Add to cart and choose Deliver as present at the checkout 2 We'll send you a voucher 3 The book will arrive at the recipient's addressYou might also be interested in
/
Paperback
10.69
€
/
Paperback
19.69
€
/
Hardback
119.09
€
/
Hardback
161.19
€
Hi! I'm Libroamiko, your book advisor.
How can I help you?