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Rule Based Classifier Analysis with Nucleotide Sequence in Normal Liver Cells and Cancer Affected Liver Cells

Mayilvaganan M , Rajamani R

The Data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. Clustering algorithm used to find groups of objects such that the objects in a group will be similar (or related) to one another and different from (or unrelated to) the objects in other groups . This paper comprises of two database such as normal liver cells and cancer affected cells. Each character variables are assigned numeric number and its corresponding pair combination of sequence are represented in a graph. In this paper ,the attempt has been made to analyze the DNA gene liver cancer dataset and normal liver cell data with reference to association and classification rule based on the FSA red algorithm and apriori algorithm. .Here this algorithm is applied to find no of occurrences for the gene dataset. After that T is replaced by U. Comparisons are made based on the Execution time and memory efficiency in finding frequent patterns. The extracted rules and analyzed results are graphically demonstrated. The performance is analyzed based on the different no of instances and confidence in DNA sequence data set.