Results 31 to 40 of about 785,617 (209)

Application of Event Based Decision Tree and Ensemble of Data Driven Methods for Maintenance Action Recommendation

International Journal of Prognostics and Health Management, 2013
This study presents the methods employed by a team from the department of Mechatronics and Dynamics at the University of Paderborn, Germany for the 2013 PHM data challenge.
James K. Kimotho, Christoph Sondermann-Woelke, Tobias Meyer, Walter Sextro   +3 more
doaj   +1 more source

Learning Explainable Decision Rules via Maximum Satisfiability

IEEE Access, 2020
Decision trees are a popular choice for providing explainable machine learning, since they make explicit how different features contribute towards the prediction.
Henrik E. C. Cao, Riku Sarlin, Alexander Jung   +2 more
doaj   +1 more source

Dynamic Decision Trees

Knowledge
Knowledge comes in various forms: scientific, artistic, legal, and many others. For most non-computer scientists, it is far easier to express their knowledge in text than in programming code.
Joseph Vidal, Spriha Jha, Zhenyuan Liang, Ethan Delgado, Bereket Siraw Deneke, Dennis Shasha   +5 more
doaj   +1 more source

Applications of Depth Minimization of Decision Trees Containing Hypotheses for Multiple-Value Decision Tables

Entropy, 2023
In this research, we consider decision trees that incorporate standard queries with one feature per query as well as hypotheses consisting of all features’ values.
Mohammad Azad, Mikhail Moshkov
doaj   +1 more source

Quantum Computation and Decision Trees

, 1998
Many interesting computational problems can be reformulated in terms of decision trees. A natural classical algorithm is to then run a random walk on the tree, starting at the root, to see if the tree contains a node n levels from the root.
Farhi, Edward, Gutmann, Sam
core   +1 more source

CSNL: A cost-sensitive non-linear decision tree algorithm [PDF]

, 2010
This article presents a new decision tree learning algorithm called CSNL that induces Cost-Sensitive Non-Linear decision trees. The algorithm is based on the hypothesis that nonlinear decision nodes provide a better basis than axis-parallel decision ...
Allwein E. L., Bennett K. P., Bradford J., Breslow L., Brown G., Elkan C., Fan W., Kanani P., Knoll U., Martin A., Masnadi-Shirazi H., Pazzani M., Provost F. J., Sunil Vadera, Ting K., Ting K., Turney P., Vadera S., Vadera S., Zadrozny B., Zhu X.   +20 more
core   +3 more sources

A multivariate approach to heavy flavour tagging with cascade training

, 2007
This paper compares the performance of artificial neural networks and boosted decision trees, with and without cascade training, for tagging b-jets in a collider experiment.
B. Roe, D.V. Bandourin, D0 collaboration, D0 collaboration, G. Cowan, I. Narsky, I. Narsky, J Bastos, J. Conrad, J. Rojo, R. Meir, R.E. Schapire, S. Forte, Y Liu, Y. Freund, Y. Liu   +15 more
core   +1 more source

Multi-test Decision Tree and its Application to Microarray Data Classification [PDF]

, 2014
Objective: The desirable property of tools used to investigate biological data is easy to understand models and predictive decisions. Decision trees are particularly promising in this regard due to their comprehensible nature that resembles the ...
Armstrong, Berzal, Breiman, Breiman, Breiman, Brodley, Brown, Brown, Che, Chen, Cohen, Cordell, Cowell, Czajkowski, Demsar, Dettling, Diaz-Uriarte, Dramiński, Fayyad, Freund, Freund, Ge, Golub, Grześ, Hall, Hastie, Hu, Kuo, Li, Marcin Czajkowski, Marek Grześ, Marek Kretowski, Murthy, Murthy, Pagallo, Qu, Quinlan, Robnik-Siikonja, Rokach, Rokach, Sebastiani, Shalev-Shwartz, Shi, Tan, Tan, Wold, Yeoh   +46 more
core   +1 more source

Topological Forest

IEEE Access, 2022
We propose a new ML model called Topological Forest that contains an ensemble of decision trees. Unlike a vanilla Random Forest, Topological Forest has a special training process that selects a smaller number of decision trees on a topological graph ...
Murat Ali Bayir, Kiarash Shamsi, Huseyincan Kaynak, Cuneyt Gurcan Akcora   +3 more
doaj   +1 more source

VHT: Vertical Hoeffding Tree

, 2016
IoT Big Data requires new machine learning methods able to scale to large size of data arriving at high speed. Decision trees are popular machine learning models since they are very effective, yet easy to interpret and visualize.
Bifet, Albert, Kourtellis, Nicolas, Morales, Gianmarco De Francisci, Murdopo, Arinto   +3 more
core   +1 more source