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Alternating decision tree

Known as: ADT, ADTree 
An alternating decision tree (ADTree) is a machine learning method for classification. It generalizes decision trees and has connections to boosting… 
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Related topics

Related topics

7 relations
Boosting (machine learning)BrownBoostDecision stumpDecision tree learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2020
2020
An Advanced Approach for Choosing Security Patterns and Checking their Implementation
This paper tackles the problems of generating concrete test cases for testing whether an application is vulnerable to attacks… 
2018
2018
Fast Counting in Machine Learning Applications
We propose scalable methods to execute counting queries in machine learning applications. To achieve memory and computational… 
2016
2016
Predictive modeling of the first year evaluation based on demographics data: Case study students of Telkom University, Indonesia
Student academic failure prediction is still interesting topics in the Educational Data Mining. One of the challenges is how to… 
2014
2014
A semantic-based approach for representing successful graduate predictive rules
This paper seeks to identify the factors of university students in major of Computer Science at Thaksin University, Thailand that… 
Review
2014
Review
2014
Diagnosis of Parkinson Disease Using Machine Learning and Data Mining Systems from Voice Dataset
Parkinson’s disease is one of the most painful, dangerous and non curable diseases which occurs at older ages (mostly above 50… 
Review
2013
Review
2013
ADTool: Security Analysis with Attack-Defense Trees
ADTool is free, open source software assisting graphical modeling and quantitative analysis of security, using attack–defense… 
2013
2013
Empirical Investigation of Decision Tree Ensembles for Monitoring Cardiac Complications of Diabetes
Cardiac complications of diabetes require continuous monitoring since they may lead to increased morbidity or sudden death of… 
2012
2012
Comparison of Classification Algorithms using WEKA on Various Datasets
: Data mining is a step in the knowledge discovery process consisting of data mining algorithms that used to finds patterns or… 
2012
2012
A fast calculation of metric scores for learning Bayesian network
Frequent counting is a very so often required operation in machine learning algorithms. A typical machine learning task, learning… 
Highly Cited
2001
Highly Cited
2001
Optimizing the Induction of Alternating Decision Trees
The alternating decision tree brings comprehensibility to the performance enhancing capabilities of boosting. A single… 
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