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PKDD
2005
Springer
142views Data Mining» more  PKDD 2005»
13 years 11 months ago
Speeding Up Logistic Model Tree Induction
Logistic Model Trees have been shown to be very accurate and compact classifiers [8]. Their greatest disadvantage is the computational complexity of inducing the logistic regressi...
Marc Sumner, Eibe Frank, Mark A. Hall
GECCO
2008
Springer
175views Optimization» more  GECCO 2008»
13 years 7 months ago
Using differential evolution for symbolic regression and numerical constant creation
One problem that has plagued Genetic Programming (GP) and its derivatives is numerical constant creation. Given a mathematical formula expressed as a tree structure, the leaf node...
Brian M. Cerny, Peter C. Nelson, Chi Zhou
AAAI
2011
12 years 6 months ago
Logistic Methods for Resource Selection Functions and Presence-Only Species Distribution Models
In order to better protect and conserve biodiversity, ecologists use machine learning and statistics to understand how species respond to their environment and to predict how they...
Steven Phillips, Jane Elith
ICONIP
2008
13 years 7 months ago
An Evaluation of Machine Learning-Based Methods for Detection of Phishing Sites
In this paper, we present the performance of machine learning-based methods for detection of phishing sites. We employ 9 machine learning techniques including AdaBoost, Bagging, S...
Daisuke Miyamoto, Hiroaki Hazeyama, Youki Kadobaya...
ICML
2004
IEEE
13 years 11 months ago
Ensembles of nested dichotomies for multi-class problems
Nested dichotomies are a standard statistical technique for tackling certain polytomous classification problems with logistic regression. They can be represented as binary trees ...
Eibe Frank, Stefan Kramer