mlrules mlrules-weka-package

Parent	oss-parent
Group	com.github.fracpete
描述	Maximum Likelihood Rule Ensembles (MLRules) is a new rule induction algorithm for solving classification problems via probability estimation. The ensemble is built using boosting, by greedily minimizing the negative loglikelihood which results in estimating the class conditional probability distribution. The main advantage of decision rules is their simplicity and comprehensibility: they are logical statements of the form "if condition then decision", which is probably the easiest form of model to interpret. On the other hand, by exploiting a powerful statistical technique to induce the rules, the final ensemble has very high prediction accuracy. Fork of the original code located at: http://www.cs.put.poznan.pl/wkotlowski/software-mlrules.html
Packaging	jar
Size	20.44 KB
文件	pom jar
网址	https://github.com/fracpete/mlrules-weka-package
发布时间	2023-07-26 06:52

dependencies

Group	Artifact	Version
nz.ac.waikato.cms.weka	weka-dev	[3.7.11,)
nz.ac.waikato.cms.weka	weka-dev	[3.7.11,)
junit	junit	4.13.1

developers

krzysztofdembczynski	Krzysztof Dembczynski
wojciechkotlowski	Wojciech Kotlowski
romanslowinski	Roman Slowinski
fracpete	Peter Reutemann

licenses

GNU General Public License 3

http://www.gnu.org/licenses/gpl-3.0.txt