Harvesting Trees gathers past and recent results on tree-based methods focalizing the attention on both the software implementation of suitable procedures for special types of data sets (i.e., complex data structure, multi-class response, set of within-groups correlated predictors, missing data) and the perception of tree results in real world case studies applications. Main issue is to make feasible the idea of trees as a powerful tool to provide information which is statistically reliable and with an added value in terms of problem solving and knowledge discovery.
Tree Harvest: Methods, Software and Some Applications
CONVERSANO, CLAUDIO
2004-01-01
Abstract
Harvesting Trees gathers past and recent results on tree-based methods focalizing the attention on both the software implementation of suitable procedures for special types of data sets (i.e., complex data structure, multi-class response, set of within-groups correlated predictors, missing data) and the perception of tree results in real world case studies applications. Main issue is to make feasible the idea of trees as a powerful tool to provide information which is statistically reliable and with an added value in terms of problem solving and knowledge discovery.
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