**387**
results

- Go to itemAODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that h…
- Go to itemAODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that h…
- Go to itemA2DE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that h…
- Go to itemA2DE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that h…
- Go to itemClass for generating an alternating decision tree. The basic algorithm is based on: Freund, Y., Mason, L.: The alternating decisi…
- Go to itemAODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that h…
- Go to itemAODEsr augments AODE with Subsumption Resolution.AODEsr detects specializations between two attribute values at classification ti…
- Go to itemClass for boosting a nominal class classifier using the Adaboost M1 method. Only nominal class problems can be tackled. Often dra…
- Go to itemClass for boosting a nominal class classifier using the Adaboost M1 method Only nominal class problems can be tackled.Often drama…
- Go to itemMeta classifier that enhances the performance of a regression base classifier. Each iteration fits a model to the residuals left …
- Go to itemMeta classifier that enhances the performance of a regression base classifier Each iteration fits a model to the residuals left b…
- Go to itemClass implementing an Apriori-type algorithm. Iteratively reduces the minimum support until it finds the required number of rules…
- Go to itemClass implementing an Apriori-type algorithm Iteratively reduces the minimum support until it finds the required number of rules …
- Go to itemDimensionality of training and test data is reduced by attribute selection before being passed on to a classifier. (based on WEKA…
- Go to itemDimensionality of training and test data is reduced by attribute selection before being passed on to a classifier (based on WEKA …
- Go to itemClass for building a best-first decision tree classifier. This class uses binary split for both nominal and numeric attributes. F…
- Go to itemClass for building a best-first decision tree classifier This class uses binary split for both nominal and numeric attributes.For…
- Go to itemBuilds a description of a Bayes Net classifier stored in XML BIF 0.3 format. For more details on XML BIF see: Fabio Cozman, Marek…
- Go to itemClass for bagging a classifier to reduce variance. Can do classification and regression depending on the base learner. For more i…
- Go to itemClass for bagging a classifier to reduce variance Can do classification and regression depending on the base learner. For more in…