Confidence factor Weka J48
,由 G Stiglic 著作 · 2012 · 被引用 133 次 — The default J48 decision tree in Weka uses pruning based on subtree raising, confidence factor of 0.25, minimal number of objects is set to ... ,Use unpruned tree. -C confidence. Set confidence threshold for pruning. (Default: 0.25). -M number. Set minimum number of instances per leaf. ( ... ,The confidence factor used for pruning (smaller values incur more pruning). debug: The value of this option is ignored in Knime. minNumObj: The minimum number ... ,J48 has the following parameters that can be adjusted. ... The higher this value, the more 'confident' you are that the data you are learning from is a good. ,2019年4月14日 — What does this value exactly mean? I know that bigger value means that I believe more my learning set is a good representation of the whole ...,Hello My question(s) concern the value of confidence when using J48 classifiers in. Weka. To give some background: I am currently Java programs to have J48 ... ,2020年1月16日 — After running J48 algorithm, I'm getting 65.07% correctly classified instances and 68.7% average roc area. I have to get this performance ... ,2020年9月24日 — 5决策树算法的实现(weka成为J48). 这里-C 0.25 是Confidence Factor=0.25. -M 2 是minNumObj=2，即the minimum number of instances per leaf. 可以在这 ...
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 Confidence factor Weka J48 相關參考資料
CLASSIFICATION USING J48| DATA MINING WITH WEKA ...
https://www.youtube.com Comprehensive Decision Tree Models in Bioinformatics
由 G Stiglic 著作 · 2012 · 被引用 133 次 — The default J48 decision tree in Weka uses pruning based on subtree raising, confidence factor of 0.25, minimal number of objects is set to ... https://www.ncbi.nlm.nih.gov J48
Use unpruned tree. -C confidence. Set confidence threshold for pruning. (Default: 0.25). -M number. Set minimum number of instances per leaf. ( ... https://weka.sourceforge.io J48 (Weka)
The confidence factor used for pruning (smaller values incur more pruning). debug: The value of this option is ignored in Knime. minNumObj: The minimum number ... https://nodepit.com J48 Classifier Parameters
J48 has the following parameters that can be adjusted. ... The higher this value, the more 'confident' you are that the data you are learning from is a good. https://www.schankacademy.com Meaning of confidence factor in J48
2019年4月14日 — What does this value exactly mean? I know that bigger value means that I believe more my learning set is a good representation of the whole ... https://stackoverflow.com Value of confidence and pruning in J48
Hello My question(s) concern the value of confidence when using J48 classifiers in. Weka. To give some background: I am currently Java programs to have J48 ... https://wekalist.scms.waikato. Weka - How can I improve J48 performance?
2020年1月16日 — After running J48 algorithm, I'm getting 65.07% correctly classified instances and 68.7% average roc area. I have to get this performance ... https://stackoverflow.com Weka(二)—Classification(糖尿病数据集&Cross-validation ...
2020年9月24日 — 5决策树算法的实现(weka成为J48). 这里-C 0.25 是Confidence Factor=0.25. -M 2 是minNumObj=2，即the minimum number of instances per leaf. 可以在这 ... https://blog.csdn.net |