Teaching AI algorithms using animations reinforced by interactive exercises
Proceedings of the 2nd Australasian conference on Computer science education
Exploration mining in diabetic patients databases: findings and conclusions
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning Structure from Data and Its Application to Ozone Prediction
Applied Intelligence
An inductive learning method for medical diagnosis
Pattern Recognition Letters
Modelling Classification Performance for Large Data Sets
WAIM '01 Proceedings of the Second International Conference on Advances in Web-Age Information Management
DS '99 Proceedings of the Second International Conference on Discovery Science
An Appropriate Abstraction for an Attribute-Oriented Induction
DS '99 Proceedings of the Second International Conference on Discovery Science
Data mining tasks and methods: Classification: the goal of classification
Handbook of data mining and knowledge discovery
Data mining from clinical data using interactive evolutionary computation
Advances in evolutionary computing
Decision tree learning with fuzzy labels
Information Sciences—Informatics and Computer Science: An International Journal
Learning with ensembles of randomized trees: new insights
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
Pattern recognition techniques for the classification of malware packers
ACISP'10 Proceedings of the 15th Australasian conference on Information security and privacy
Uncertainty in decision tree classifiers
SUM'10 Proceedings of the 4th international conference on Scalable uncertainty management
Spatial decision forests for MS lesion segmentation in multi-channel MR images
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
A modular decision-tree architecture for better problem understanding
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
Mining closed discriminative dyadic sequential patterns
Proceedings of the 14th International Conference on Extending Database Technology
Purifying data by machine learning with certainty levels
Proceedings of the Third International Workshop on Reliability, Availability, and Security
Proceedings of the 20th international conference companion on World wide web
Active rule learning using decision tree for resource management in Grid computing
Future Generation Computer Systems
A dynamic sliding window approach for activity recognition
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
Fuzzy ID3 algorithm based on generating Hartley measure
WISM'11 Proceedings of the 2011 international conference on Web information systems and mining - Volume Part II
MLMI'11 Proceedings of the Second international conference on Machine learning in medical imaging
Expert Systems with Applications: An International Journal
A fractal dimension based filter algorithm to select features for supervised learning
IBERAMIA-SBIA'06 Proceedings of the 2nd international joint conference, and Proceedings of the 10th Ibero-American Conference on AI 18th Brazilian conference on Advances in Artificial Intelligence
Data Mining and Knowledge Discovery
Future Generation Computer Systems
Learning strategies for task delegation in norm-governed environments
Autonomous Agents and Multi-Agent Systems
Incrementally optimized decision tree for noisy big data
Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications
Incrementally optimized decision tree for noisy big data
Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications
Transactional auto scaler: elastic scaling of in-memory transactional data grids
Proceedings of the 9th international conference on Autonomic computing
Statistical cross-language Web content quality assessment
Knowledge-Based Systems
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From the Publisher:Classifier systems play a major role in machine learning and knowledge-based systems, and Ross Quinlan's work on ID3 and C4.5 is widely acknowledged to have made some of the most significant contributions to their development. This book is a complete guide to the C4.5 system as implemented in C for the UNIX environment. It contains a comprehensive guide to the system's use , the source code (about 8,800 lines), and implementation notes. The source code and sample datasets are also available on a 3.5-inch floppy diskette for a Sun workstation. C4.5 starts with large sets of cases belonging to known classes. The cases, described by any mixture of nominal and numeric properties, are scrutinized for patterns that allow the classes to be reliably discriminated. These patterns are then expressed as models, in the form of decision trees or sets of if-then rules, that can be used to classify new cases, with emphasis on making the models understandable as well as accurate. The system has been applied successfully to tasks involving tens of thousands of cases described by hundreds of properties. The book starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting. Advantages and disadvantages of the C4.5 approach are discussed and illustrated with several case studies. This book and software should be of interest to developers of classification-based intelligent systems and to students in machine learning and expert systems courses.