Results 51 to 60 of about 1,307,990 (175)
Engineering and Applied Science Research, 2022 Decision Trees are a common approach used for classifying unseen data into defined classes. The Information Gain is usually applied as splitting criteria in the node selection process for constructing the decision tree.
Sirichanya Chanmee, Kraisak Kesorn
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Decision Tree Algorithm Considering Distances Between Classes
IEEE Access, 2022 Decision tree algorithm (DT) is a commonly used data mining method for classification and regression. DT repeatedly divides a dataset into pure subsets based on impurity measurements such as entropy and Gini.
Sangyong Lee +3 more
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A Comparison of the Use of Binary Decision Trees and Neural Networks in Top Quark Detection
, 1992 The use of neural networks for signal vs.~background discrimination in high-energy physics experiment has been investigated and has compared favorably with the efficiency of traditional kinematic cuts.
D. E. Rumelhart +8 more
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MAPTree: Beating “Optimal” Decision Trees with Bayesian Decision Trees
Proceedings of the AAAI Conference on Artificial IntelligenceDecision trees remain one of the most popular machine learning models today, largely due to their out-of-the-box performance and interpretability. In this work, we present a Bayesian approach to decision tree induction via maximum a posteriori inference of a posterior distribution over trees.
Sullivan, Colin +2 more
openaire +2 more sources
A Chi-MIC Based Adaptive Multi-Branch Decision Tree
IEEE Access, 2021 Since the decision trees (DTs) have an advantage over “black-box” models, such as neural nets or support vector machines, in terms of comprehensibility, such that it might merit improvement for further optimization.
Jiahao Ye +6 more
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Decision tree analysis for prostate cancer prediction [PDF]
Srpski Arhiv za Celokupno Lekarstvo, 2019 Introduction/Objective. The use of serum prostate-specific antigen (PSA) test has dramatically increased the number of men undergoing prostate biopsy. However, the best possible strategies for selecting appropriate patients for prostate biopsy have yet ...
Stojadinović Miroslav M. +2 more
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, 2020 Decision tree algorithms have been among the most popular algorithms for interpretable (transparent) machine learning since the early 1980's. The problem that has plagued decision tree algorithms since their inception is their lack of optimality, or lack
Hu, Xiyang +2 more
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A comparative evaluation of deep and shallow approaches to the automatic detection of common grammatical errors [PDF]
, 2007 This paper compares a deep and a shallow processing approach to the problem of classifying a sentence as grammatically wellformed or ill-formed. The deep processing approach uses the XLE LFG parser and English grammar: two versions are presented, one ...
Foster, Jennifer +2 more
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ANALYZING BIG DATA WITH DECISION TREES [PDF]
, 2014 ANALYZING BIG DATA WITH DECISION ...
Leong, Lok Kei
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Decision Tree Classifiers for Star/Galaxy Separation
, 2010 We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS DR7). Each algorithm is defined by a set of parameters which, when varied,
Abazajian +39 more
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