C4.5: programs for machine learning
C4.5: programs for machine learning
Data mining and knowledge discovery in databases
Communications of the ACM
Automated detection of hereditary syndromes using data mining
Computers and Biomedical Research
Principles of data mining
A divisive information theoretic feature clustering algorithm for text classification
The Journal of Machine Learning Research
Stability-based validation of clustering solutions
Neural Computation
Diagnosis of the diseases: using a GA-fuzzy approach
Information Sciences: an International Journal - Special issue: Medical expert systems
Unlabeled Data Classification via Support Vector Machines and k-means Clustering
CGIV '04 Proceedings of the International Conference on Computer Graphics, Imaging and Visualization
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Enhancement of a Chinese discourse marker tagger with C4.5
CLPW '00 Proceedings of the second workshop on Chinese language processing: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 12
Artificial Intelligence in Recognition and Classification of Astrophysical and Medical Images (Studies in Computational Intelligence)
IEEE Transactions on Knowledge and Data Engineering
Breast cancer diagnosis using least square support vector machine
Digital Signal Processing
Using clustering to enhance text classification
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Computer Methods and Programs in Biomedicine
Design of a hybrid system for the diabetes and heart diseases
Expert Systems with Applications: An International Journal
Developing fuzzy classifiers to predict the chance of occurrence of adult psychoses
Knowledge-Based Systems
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Effective diagnosis of heart disease through neural networks ensembles
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Improved use of continuous attributes in C4.5
Journal of Artificial Intelligence Research
Predicting breast cancer survivability: a comparison of three data mining methods
Artificial Intelligence in Medicine
A New Approach: Role of Data Mining in Prediction of Survival of Burn Patients
Journal of Medical Systems
DEXA'07 Proceedings of the 18th international conference on Database and Expert Systems Applications
Association rule mining to detect factors which contribute to heart disease in males and females
Expert Systems with Applications: An International Journal
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The method of processing two algorithms within a single workflow, and hence the combined method, is called as hybrid computing. We propose a data mining framework comprising of two stages, namely clustering and classification. The first stage employs k-means algorithm on data and generates two clusters, namely cluster-0 and cluster-1. Instances in cluster-0 do not have disease symptoms and cluster-1 consists of instances with disease symptoms. The verification of valid grouping is then carried out by referring to the association of class labels in original datasets. Incorrectly classified instances are removed and remaining instances are used to build the classifier using C4.5 decision-tree algorithm with k-fold cross validation method. The framework was tested using eight datasets from the machine learning repository of the UCI. The proposed framework was evaluated for accuracy, sensitivity and specificity measures. Our framework obtained promising classification accuracy as compared to other methods found in the literature.