Multivariate alternating decision trees
作者：
Highlights：
• Novel concept of multivariate alternating decision tree (ADTree) with boosting.
• Offering high prediction accuracy similar to decision tree ensembles.
• Retaining good comprehension similar to individual univariate decision trees.
• Bridging powerful regularization techniques to decision tree research.
• Introduction and validation of multivariate ADTree algorithms on public datasets.
摘要
•Novel concept of multivariate alternating decision tree (ADTree) with boosting.•Offering high prediction accuracy similar to decision tree ensembles.•Retaining good comprehension similar to individual univariate decision trees.•Bridging powerful regularization techniques to decision tree research.•Introduction and validation of multivariate ADTree algorithms on public datasets.
论文关键词：Alternating decision tree,Boosting,Multivariate decision tree,Lasso,LARS
论文评审过程：Received 5 May 2015, Revised 7 July 2015, Accepted 17 August 2015, Available online 28 August 2015, Version of Record 5 November 2015.
论文官网地址：https://doi.org/10.1016/j.patcog.2015.08.014
