AVD — A New Classification Algorithm
S. Pramala, B. Rajalakshmi, S. Balamurugan · ASME Press eBooks · 2011
This paper proposes a new classification algorithm named the Attribute Value Dependant classifier (AVD). This AVD classifier mainly focuses on identifying the relationship between the attribute values in the training dataset and the class label values. The ‘Attribute Value Dependant’ is the value which determines the extent to which each attribute value has its impact in deciding the class label is identified; and the training model is built based on these values. The attribute values in the test dataset are compared against the ‘Attribute Value Dependant’ values and based on this comparison the test dataset is classified. Since individual attribute value dependency on the class label is found, the irrelevant and inconsistent data in the training dataset are ignored during the classification and consequently the classification accuracy is improved. The performance of the AVD classifier has been compared with seven traditional classifiers and has been proved to produce better results.