Search

Your search keyword '"Herrera, Francisco"' showing total 4 results
Start Over Author "Herrera, Francisco" Topic artificial intelligence Topic data mining
4 results on '"Herrera, Francisco"'

1. Special issue: Data mining and hybrid intelligent systems.

Author

Xhafa, Fatos, Herrera, Francisco, and Köppen, Mario

Subjects
*ARTIFICIAL intelligence, *DATA mining
Abstract

The article discusses various papers published within the issue, including one on support vector machines, one on the analysis of the evolutionary learning algorithm XCS and one two more on case-based reasoning.

Published
2009
Full Text
View/download PDF

2. Data Science Institutes and Data Centers

Author

Earnshaw, Rae, Jain, Lakhmi C., Editor-in-Chief, Wu, Xindong, Editor-in-Chief, Brahnam, Sheryl, Series Editor, Cook, Diane J, Series Editor, Domingo-Ferrer, Josep, Series Editor, Gabrys, Bogdan, Series Editor, Herrera, Francisco, Series Editor, Mamitsuka, Hiroshi, Series Editor, Phoha, Vir V., Series Editor, Siebes, Arno, Series Editor, de Wilde, Philippe, Series Editor, Earnshaw, Rae, Dill, John, and Kasik, David

Published
2019
Full Text
View/download PDF

3. Decision Trees in Stock Market Analysis: Construction and Validation

Author

Miró-Julià, Margaret, Fiol-Roig, Gabriel, Isern-Deyà, Andreu Pere, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, García-Pedrajas, Nicolás, editor, Herrera, Francisco, editor, Fyfe, Colin, editor, Benítez, José Manuel, editor, and Ali, Moonis, editor

Published
2010
Full Text
View/download PDF

4. Ensembles of Probability Estimation Trees for Customer Churn Prediction

Author

Koen W. De Bock, Dirk Van den Poel, García-Pedrajas, Nicolás, Herrera, Francisco, Fyfe, Colin, Benítez, José Manuel, and Ali, Moonis

Subjects
database marketing, Probability estimation, Computer science, business.industry, Lift (data mining), RANKING, Decision tree, PETs, Science General, Machine learning, computer.software_genre, lift, Random subspace method, CRM, ComputingMethodologies_PATTERNRECOGNITION, Ranking, FORESTS, churn prediction, probability estimation trees, ensemble classification, AdaBoost, Artificial intelligence, Data mining, business, computer
Abstract

Customer churn prediction is one of the most, important elements tents of a company's Customer Relationship Management, (CRM) strategy In tins study, two strategies are investigated to increase the lift. performance of ensemble classification models, i.e (1) using probability estimation trees (PETs) instead of standard decision trees as base classifiers; and (n) implementing alternative fusion rules based on lift weights lot the combination of ensemble member's outputs Experiments ale conducted lot font popular ensemble strategics on five real-life chin n data sets In general, the results demonstrate how lift performance can be substantially improved by using alternative base classifiers and fusion tides However: the effect vanes lot the (Idol cut ensemble strategies lit particular, the results indicate an increase of lift performance of (1) Bagging by implementing C4 4 base classifiets. (n) the Random Subspace Method (RSM) by using lift-weighted fusion rules, and (in) AdaBoost, by implementing both.

Published
2010

Catalog

Books, media, physical & digital resources
See catalog results