INDECISIVE CONDITION CLASSIFICATION USING SVM
- Jyoti Pathak
- Sachin Patel
support vector machine, indecisive data, associative classification, fuzzy clustering.
In this research, we exploit the regularize framework and proposed an associative classification algorithm for uncertain data. The major recompense of SVM(support vector machine) are: recurrent item sets capture every dominant associations between items in a dataset. These classifiers naturally handle missing values and outliers as they only deal with statistically significant associations which build the classification to be vigorous. We proposed a novel indecisive SVM Based clustering algorithm which considers large databases as the major application. The SVM Based clustering algorithm will cluster a specified set of data and exploit the matching which proposes other works.
Volume 2 Issue 1
Pages. 688-693