Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
Data Mining and Knowledge Discovery
Sequential Decision Models for Expert System Optimization
IEEE Transactions on Knowledge and Data Engineering
An Instance-Weighting Method to Induce Cost-Sensitive Trees
IEEE Transactions on Knowledge and Data Engineering
Learning Patterns of Behavior by Observing System Events
ECML '00 Proceedings of the 11th European Conference on Machine Learning
DS '98 Proceedings of the First International Conference on Discovery Science
Connectionist and evolutionary models for learning, discovering and forecasting software effort
Managing data mining technologies in organizations
The Knowledge Engineering Review
Decision trees with minimal costs
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Cost-Constrained Data Acquisition for Intelligent Data Preparation
IEEE Transactions on Knowledge and Data Engineering
"Missing Is Useful': Missing Values in Cost-Sensitive Decision Trees
IEEE Transactions on Knowledge and Data Engineering
Hybrid approaches for classification under information acquisition cost constraint
Decision Support Systems
Test-Cost Sensitive Classification on Data with Missing Values
IEEE Transactions on Knowledge and Data Engineering
Feature value acquisition in testing: a sequential batch test algorithm
ICML '06 Proceedings of the 23rd international conference on Machine learning
Learning accurate and concise naïve Bayes classifiers from attribute value taxonomies and data
Knowledge and Information Systems
Utilizing hierarchical feature domain values for prediction
Data & Knowledge Engineering
A framework for the automated generation of power-efficient classifiers for embedded sensor nodes
Proceedings of the 5th international conference on Embedded networked sensor systems
Multi-group support vector machines with measurement costs: A biobjective approach
Discrete Applied Mathematics
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Multi-dimensional features reduction of PCA on SVM classifier for imaging surveillance application
ISPRA'08 Proceedings of the 7th WSEAS International Conference on Signal Processing, Robotics and Automation
Test-Cost Sensitive Classification Based on Conditioned Loss Functions
ECML '07 Proceedings of the 18th European conference on Machine Learning
Building a cost-constrained decision tree with multiple condition attributes
Information Sciences: an International Journal
A hierarchical model for test-cost-sensitive decision systems
Information Sciences: an International Journal
Cost-sensitive test strategies
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Integrating learning from examples into the search for diagnostic policies
Journal of Artificial Intelligence Research
Anytime induction of low-cost, low-error classifiers: a sampling-based approach
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
Hybrid approaches for classification under information acquisition cost constraint
Decision Support Systems
Application of Support Vector Machine classifier for security surveillance system
ACST '08 Proceedings of the Fourth IASTED International Conference on Advances in Computer Science and Technology
CSNL: A cost-sensitive non-linear decision tree algorithm
ACM Transactions on Knowledge Discovery from Data (TKDD)
Cost-time sensitive decision tree with missing values
KSEM'07 Proceedings of the 2nd international conference on Knowledge science, engineering and management
Cost-sensitive classification with respect to waiting cost
Knowledge-Based Systems
Qualitative test-cost sensitive classification
Pattern Recognition Letters
Learning to learn decision trees
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Comprehensibility improvement of tabular knowledge bases
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Test-cost sensitive classification on data with missing values in the limited time
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
Test-cost sensitive classification using greedy algorithm on training data
ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
Cost sensitive classification in data mining
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications: Part I
Expert Systems with Applications: An International Journal
Costs-sensitive classification in multistage classifier with fuzzy observations of object features
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
ACE-Cost: acquisition cost efficient classifier by hybrid decision tree with local SVM leaves
MLDM'11 Proceedings of the 7th international conference on Machine learning and data mining in pattern recognition
Journal of Artificial Intelligence Research
SEWEBAR-CMS: semantic analytical report authoring for data mining results
Journal of Intelligent Information Systems
Evolutionary induction of cost-sensitive decision trees
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Cost-Sensitive decision tree learning for forensic classification
ECML'06 Proceedings of the 17th European conference on Machine Learning
Hybrid cost-sensitive decision tree
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
Decision tree classifiers sensitive to heterogeneous costs
Journal of Systems and Software
Ontology-Enhanced association mining
EWMF'05/KDO'05 Proceedings of the 2005 joint international conference on Semantics, Web and Mining
Cost-sensitive classification with unconstrained influence diagrams
SOFSEM'12 Proceedings of the 38th international conference on Current Trends in Theory and Practice of Computer Science
Comparison of cost for zero-one and stage-dependent fuzzy loss function
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part I
Learning strategies for task delegation in norm-governed environments
Autonomous Agents and Multi-Agent Systems
A competition strategy to cost-sensitive decision trees
RSKT'12 Proceedings of the 7th international conference on Rough Sets and Knowledge Technology
Cost-Sensitive splitting and selection method for medical decision support system
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Cost-sensitive decision trees applied to medical data
DaWaK'07 Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery
The CASH algorithm-cost-sensitive attribute selection using histograms
Information Sciences: an International Journal
Cost-sensitive decision tree ensembles for effective imbalanced classification
Applied Soft Computing
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At present, algorithms of the ID3 family are not based on background knowledge. For that reason, most of the time they are neither logical nor understandable to experts. These algorithms cannot perform different types of generalization as others can do (Michalski, 1983; Kodratoff, 1983), nor can they can reduce the cost of classifications. The algorithm presented in this paper tries to generate more logical and understandable decision trees than those generated by ID3-like algorithms; it executes various types of generalization and at the same time reduces the classification cost by means of background knowledge. The background knowledge contains the ISA hierarchy and the measurement cost associated with each attribute. The user can define the degrees of economy and generalization. These data will influence directly the quantity of search that the algorithm must undertake. This algorithm, which is an attribute version of the EG2 method (Núñez, 1988a, 1988b), has been implemented and the results appear in this paper comparing them with other methods.