Decision treesRandom forestDecision trees and their ensembles are very popular models of supervised machine learning. In this paper we merge the ideas underlying decision trees, their ensembles and FCA by proposing a new supervised machine learning model which can be constructed in polynomial time and...
2002. Building decision tree classifier on private data. In Proceedings of the IEEE International Conference on Privacy, Security and Data Mining - Volume 14 (CRPIT’02). Australian Computer Society, Inc., Darlinghurst, Australia, Australia, 1–8. http://dl.acm.org/citation.cfm?id=850782.850784...
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes...
[17] Wenliang Du and Zhijun Zhan. 2002. Building Decision Tree Classifier on Private Data. In Proceedings of the IEEE International Conference on Privacy, Security and Data Mining - Volume 14 (CRPIT ’14). Australian Computer Society, Inc., Darlinghurst, Australia, Australia, 1–8. http://dl...
In the case of real-world data streams, the underlying data distribution will not be static; it is subject to variation over time, which is known as the primary reason for concept drift. Concept drift poses severe problems to the accuracy of a model in online learning scenarios. The recurrin...
Towards Automated Concept-based Decision TreeExplanations for CNNs In addition, ACDTE generates counterfactual explanations, suggesting the the minimum changes in the instance's concept-based explanation that lead to a different prediction. Our experiments demonstrate that such a shallow decision tree is...
Assaghir, Kaytoue, Meira, and Villerd (2011) did an exploratory study on the possibilities of decision tree induction from numerical data by using interval pattern structures. Interval pattern structures are used to extract sets of minimal positive and negative hypotheses. They then propose an ...
Therefore, in general, concept maps are structured as networks and only by adopting a specific discipline in the process of building a map is it possible to obtain a hierarchical map or a tree-structured map. There are different software tools for building concept maps and operating on them. ...
The main purpose of the algorithm is to construct the weighted FP tree, while the time consumed in data reading, CD detection and drift adaptation to the modules is small. These processing steps are characterized by an overall fast calculation speed and a high processing efficiency, so the ...
The Concept of Childhood in Western CountriesThe history of childhood has been a heated topic in social history since the highly influential book Centuries of Childhood’, written by French historia…