Results 81 to 90 of about 4,693,052 (300)
A New Algorithm for Optimization of Fuzzy Decision Tree in Data Mining [PDF]
Journal of Optimization in Industrial Engineering, 2011 Decision-tree algorithms provide one of the most popular methodologies for symbolic knowledge acquisition. The resulting knowledge, a symbolic decision tree along with a simple inference mechanism, has been praised for comprehensibility.
Abolfazl Kazemi, Elahe Mehrzadegan
doaj
A Novel Hyperparameter-Free Approach to Decision Tree Construction That Avoids Overfitting by Design
IEEE Access, 2019 Decision trees are an extremely popular machine learning technique. Unfortunately, overfitting in decision trees still remains an open issue that sometimes prevents achieving good performance.
Rafael Garcia Leiva +3 more
doaj +1 more source
Succinct Explanations With Cascading Decision Trees [PDF]
arXiv, 2020 The decision tree is one of the most popular and classical machine learning models from the 1980s. However, in many practical applications, decision trees tend to generate decision paths with excessive depth. Long decision paths often cause overfitting problems, and make models difficult to interpret.
arxiv
Monotone Classification with Decision Trees [PDF]
Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology, 2013 In machine learning, monotone classification is concerned with a classification function to learn in order to guarantee a kind of monotonicity of the class with respect to attribute values. In this paper, we focus on rank discrimination measures to be used in decision tree induction, i.e., functions able to measure the discrimination power of an ...
Christophe, Marsala, PETTURITI, DAVIDE
openaire +5 more sources
Using deep learning generated CBCT contours for online dose assessment of prostate SABR treatments
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Prostate Stereotactic Ablative Body Radiotherapy (SABR) is an ultra‐hypofractionated treatment where small setup errors can lead to higher doses to organs at risk (OARs). Although bowel and bladder preparation protocols reduce inter‐fraction variability, inconsistent patient adherence still results in OAR variability.
Conor Sinclair Smith +8 more
wiley +1 more source
Behavior Trees for Smart Robots Practical Guidelines for Robot Software Development
Journal of Robotics, 2022 Behavior Trees are a promising approach to model the autonomous behaviour of robots in dynamic environments. Behavior Trees represent action selection decisions as a tree of decision nodes.
Eric Dortmans, Teade Punter
doaj +1 more source
Bounds on Depth of Decision Trees Derived from Decision Rule Systems [PDF]
arXiv, 2023 Systems of decision rules and decision trees are widely used as a means for knowledge representation, as classifiers, and as algorithms. They are among the most interpretable models for classifying and representing knowledge. The study of relationships between these two models is an important task of computer science. It is easy to transform a decision
arxiv
Deep Neural Network Initialization With Decision Trees
IEEE Transactions on Neural Networks and Learning Systems, 2017 In this paper, a novel, automated process for constructing and initializing deep feedforward neural networks based on decision trees is presented.
K. Humbird, J. L. Peterson, R. McClarren
semanticscholar +1 more source
Decision Trees for Uncertain Data [PDF]
2009 IEEE 25th International Conference on Data Engineering, 2009 Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information. Value uncertainty arises in many applications during the data collection process. Example sources of uncertainty include measurement/quantization errors, data staleness, and multiple repeated ...
Tsang, S +4 more
openaire +5 more sources
An anonymization technique using intersected decision trees
Journal of King Saud University: Computer and Information Sciences, 2015 Data mining plays an important role in analyzing the massive amount of data collected in today’s world. However, due to the public’s rising awareness of privacy and lack of trust in organizations, suitable Privacy Preserving Data Mining (PPDM) techniques
Sam Fletcher, Md Zahidul Islam
doaj +1 more source