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Test strategies for cost-sensitive decision trees
2006
IEEE Transactions on Knowledge and Data Engineering
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We first propose a lazy decision tree learning algorithm that minimizes the sum of attribute costs and misclassification costs. ...
cost for test examples (new patients). ...
ACKNOWLEDGMENTS The authors would like to thank Peter Turney for his helpful discussions and suggestions during this research. They also thank reviewers for insightful comments. Charles X. ...
doi:10.1109/tkde.2006.131
fatcat:7izaxjguurbx7ewj4o6maioeja
Simple Test Strategies for Cost-Sensitive Decision Trees
[chapter]
2005
Lecture Notes in Computer Science
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We study cost-sensitive learning of decision trees that incorporate both test costs and misclassification costs. ...
In particular, we first propose a lazy decision tree learning that minimizes the total cost of tests and misclassifications. ...
If its value is known in testExample, its test cost is assigned as 0
2. call CSDT(Examples, Attributes, TestCostsUpdated) to build a cost-sensitive
decision tree
CSDT(Examples, Attributes, TestCosts ...
doi:10.1007/11564096_36
fatcat:j56ps3ndu5f2tplzvtkzpzsxl4
Hybrid Cost-Sensitive Decision Tree
[chapter]
2005
Lecture Notes in Computer Science
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Cost-sensitive decision tree and cost-sensitive naïve Bayes are both new cost-sensitive learning models proposed recently to minimize the total cost of test and misclassifications. ...
decision tree and of the cost-sensitive naïve Bayes together. ...
The left part is a cost-sensitive decision tree which is used for finding the required tests for each testing example. ...
doi:10.1007/11564126_29
fatcat:2zr56yinfbf53axlawzjizswta
"Missing is useful": missing values in cost-sensitive decision trees
2005
IEEE Transactions on Knowledge and Data Engineering
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We discuss and compare several strategies that utilize only known values and that "missing is useful" for cost reduction in cost-sensitive decision tree learning. ...
In this paper, we study this issue in costsensitive learning that considers both test costs and misclassification costs. ...
Thus, cost-sensitive decision tree learning algorithms would only need the known values and take advantage of "missing is useful" for cost reduction. ...
doi:10.1109/tkde.2005.188
fatcat:cgllxyzgobcaxkshtkxnxxhq7a
A Strategy of Constructing Heterogeneous Cost-Sensitive Decision Tree
2013
Advanced Materials Research
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In this paper, a strategy of constructing heterogeneous cost-sensitive decision tree is designed and the different cost are take into account together in split attribute selection. ...
Usually, the algorithm of constructing cost-sensitive decision tree assume that all types of cost can be converted into a unified units of the same price, apparently how to construct an cost conversion ...
The structure algorithm of heterogeneous cost sensitive decision tree is described in Algorithm.1 Algorithm.1heterogeneous cost sensitive decision tree 1 Create a root node N 2 If the training set is empty ...
doi:10.4028/www.scientific.net/amr.756-759.3414
fatcat:bw7rnccluvc2nfejl5xuatbqne
A decision analysis model for diagnostic strategies using DNA testing for hereditary haemochromatosis in at risk populations
2008
QJM: Quarterly journal of medicine
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For family testing, the DNA strategy is cost saving for the offspring of the proband but not for siblings. ...
Methods: Decision analytic models were constructed to compare the costs and consequences of the diagnostic strategies for a hypothetical cohort of people with suspected haemochromatosis. ...
We would also like to thank staff at the Wessex Institute for Health Research and Development and to the two anonymous referees for their helpful comments and suggestions. ...
doi:10.1093/qjmed/hcn070
pmid:18522976
fatcat:b2zwsqsggjftzbrireini2lqsu
Test-cost sensitive classification on data with missing values
2006
IEEE Transactions on Knowledge and Data Engineering
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We empirically evaluate the test-cost-sensitive methods for handling missing values on several data sets. ...
In this paper, we consider how to integrate test-cost-sensitive learning with the handling of missing values in a unified framework that includes model building and a testing strategy. ...
ACKNOWLEDGMENTS The authors would like to thank Hong Kong RGC for their support under grant No. HKUST 6187/04E. They also thank the anonymous referees for their comments. ...
doi:10.1109/tkde.2006.84
fatcat:m3tusoui4re6jngjxggedzpeui
Adeno-associated Viral-mediated Gene Transfer for Hemophilia
2007
Oncology & Hematology Review (US)
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Its methodology allows one to go from clinical observation to a decision tree framed in the form of either a cost-effectiveness or cost-utility analysis. ...
Following guidelines from the Panel on Cost-Effectiveness in Health and Medicine, we were able to demonstrate that, compared with not testing for von Willebrand disease (VWD), universal screening for VWD ...
The competing strategies were not testing or testing for VWD. ...
doi:10.17925/ohr.2007.01.01.21
fatcat:k7vls2tr3zenfoeu7jtqskgrfe
Economic evaluation of the use of PCR assay in diagnosing pulmonary TB in a low-incidence area
2004
European Respiratory Journal
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A decision tree model based on retrospective laboratory data was developed to assess the strategies of testing patients with suspicion of TB. ...
According to sensitivity analyses, reducing PCR test price, shortening test performance time or increasing the proportion of smear-positive patients in the tested population would contribute to cost savings ...
In this analysis, the tree was used to calculate the expected cost per patient and the probability of correct treatment and isolation decisions for each strategy. ...
doi:10.1183/09031936.04.00009704
pmid:15065837
fatcat:adnexifvbjhuhkvadgpefyhame
A Cost-Sensitive Decision Tree Learning Algorithm Based on a Multi-Armed Bandit Framework
2016
Computer journal
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This paper develops a new algorithm for inducing cost-sensitive decision trees that is inspired by the multi-armed bandit problem, in which a player in a casino has to decide which slot machine (bandit ...
based on accuracy and decisions based on costs can be found. ...
COST-SENSITIVE DECISION TREE LEARNING USING PRINCIPLES FROM THE MULTI-ARMED BANDIT PROBLEM This section develops the algorithm for cost-sensitive decision tree induction which uses the principles of the ...
doi:10.1093/comjnl/bxw015
fatcat:ns6g4uz7g5bc5nvbq7rdhjtt5m
Cost-sensitive C4.5 with post-pruning and competition
[article]
2012
arXiv
pre-print
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cost-sensitive decision tree with low cost. ...
Second, we design a post-pruning strategy through considering the tradeoff between test costs and misclassification costs of the generated decision tree. In this way, the total cost is reduced. ...
Its purpose is to reduce the total cost of cost-sensitive decision tree. ...
arXiv:1211.4122v1
fatcat:5k5thfd6grbtzaal3vmu4vcaza
Decision Analytic Model for Evaluation of Suspected Coronary Disease with Stress Testing and Coronary CT Angiography
2010
Academic Radiology
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FigureFigure 1 . 1 Decision tree for the work-up of symptomatic CAD. The decision tree begins on the left side with a decision node -the rectangular box -where a CAD work-up strategy is chosen. ...
The decision tree begins with a decision node -the rectangular box -where a CAD work-up strategy is chosen. ...
doi:10.1016/j.acra.2009.12.015
pmid:20171906
fatcat:aqaigkwvz5eklfdhenbw4maedm
The Cost-Effective Use of 18F-FDG PET in the Presurgical Evaluation of Medically Refractory Focal Epilepsy
2008
Journal of Nuclear Medicine
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Decision tree sensitivity analysis compared 3 imaging strategies with a baseline strategy of medical therapy for all: video-electroencephalography monitoring (VEM)/MRI strategy, in which patients underwent ...
This study applied decision tree analysis to evaluate the sensitivity, specificity, and cost-effectiveness of clinical algorithms that incorporate 18 F-FDG PET. ...
Vincent's Hospital Melbourne, for performing the neurosurgical resections on the patients reported in this series. ...
doi:10.2967/jnumed.107.048207
pmid:18483097
fatcat:3hr5a2zbhveypnf2bkpqbki67y
Enhancing Greedy Policy Techniques for Complex Cost-Sensitive Problems
[chapter]
2008
Greedy Algorithms
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The remainder of the chapter is structured as follows: section 2 reviews the search problem, and a few fundamental strategies, and provides basic definitions for data mining and decision trees. ...
There are various types of costs involved in inductive concept learning, but, for the domains we focus on, the most important are test costs and misclassification costs. ...
The technique combines two different components, on two levels: • On the bottom level, a test cost-sensitive decision tree performs a greedy search in the space of decision trees • On the top level, the ...
doi:10.5772/6357
fatcat:kgswd7govncwtcau2gko5l3abi
Cost comparison of MRSA screening and management – a decision tree analysis
2012
BMC Health Services Research
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For this cost analysis a decision analytic cost model was developed, primary based on data from peer-reviewed literature. ...
Methods: Aim of this study was to determine which MRSA screening and management strategy causes the lowest expected cost for a hospital. ...
decision-tree model. ...
doi:10.1186/1472-6963-12-438
pmid:23198880
pmcid:PMC3553071
fatcat:bvmrkkj2iraqlg62l3lckrss4y
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