**37**
results

- Go to itemLearns Gradient Boosted Trees with the objective of classification. The algorithm uses very shallow regression trees and a specia…0
- Go to itemLearns Gradient Boosted Trees with the objective of regression. The algorithm uses very shallow regression trees and a special fo…0
- Go to itemLearns Gradient Boosted Trees with the objective of regression. The algorithm uses very shallow regression trees and a special fo…0
- Go to itemLearns Gradient Boosted Trees with the objective of classification. The algorithm uses very shallow regression trees and a specia…0
- Go to itemClassifies data using a Gradient Boosted Trees model. The implementation follows the algorithms described in "Greedy Function App…0
- Go to itemApplies regression from a Gradient Boosted Trees model. The implementation follows the algorithms described in "Greedy Function A…0
- Go to itemClassifies data using a Gradient Boosted Trees model. The implementation follows the algorithms described in "Greedy Function App…0
- Go to itemClassifies data using a Gradient Boosted Trees model. The implementation follows the algorithms described in "Greedy Function App…0
- Go to itemWrites a Gradient Boosted Trees model to PMML. Models learned on bit-, byte- or double-vector columns can be translated but the n…0
- Go to itemApplies classification from a Gradient Boosted Trees model that is provided in PMML format. Note that it is currently not possibl…0
- Go to itemApplies regression from a Gradient Boosted Trees model that is provided in PMML format. Note that it is currently not possible to…0
- Go to itemApplies classification from a Gradient Boosted Trees model that is provided in PMML format. Note that it is currently not possibl…0
- Go to itemApplies classification from a Gradient Boosted Trees model that is provided in PMML format. Note that it is currently not possibl…0
- Go to itemCreates a distance measure based on the proximity induced by the given random forest* model. The proximity of two rows is the num…0
- Go to itemLearns a random forest*, which consists of a chosen number of decision trees. Each of the decision tree models is built with a di…0
- Go to itemLearns a random forest* (an ensemble of decision trees) for regression. Each of the decision tree models is built with a differen…0
- Go to itemLearns a random forest* (an ensemble of decision trees) for regression. Each of the regression tree models is learned on a differ…0
- Go to itemLearns a random forest*, which consists of a chosen number of decision trees. Each of the decision tree models is learned on a di…0
- Go to itemLearns a random forest*, which consists of a chosen number of decision trees. Each of the decision tree models is learned on a di…0
- Go to itemPredicts patterns according to an aggregation of the predictions of the individual trees in a random forest* model. (*) RANDOM FO…0