Performance Analysis and Evaluation of Different Data Mining Algorithms used for Cancer Classification

Classification algorithms of data mining have been successfully applied in the recent years to predict cancer based on the gene expression data. Micro-array is a powerful diagnostic tool that can generate handful information of gene expression of all the human genes in a cell at once. Various classification algorithms can be applied on such micro-array data to devise methods that can predict the occurrence of tumor. However, the accuracy of such methods differ according to the classification algorithm used. Identifying the best classification algorithm among all available is a challenging task. In this study, we have made a comprehensive comparative analysis of 14 different classification algorithms and their performance has been evaluated by using 3 different cancer data sets. The results indicate that none of the classifiers outperformed all others in terms of the accuracy when applied on all the 3 data sets. Most of the algorithms performed better as the size of the data set is increased. We recommend the users not to stick to a particular classification method and should evaluate different classification algorithms and select the better algorithm.

@article{Nookala2013,
  title     = {Performance Analysis and Evaluation of Different Data Mining Algorithms used for Cancer Classification},
  journal   = {International Journal of Advanced Research in Artificial Intelligence},
  volume    = {2},
  number    = {5},
  year      = {2013},
  publisher = {The Science and Information Organization},
  author    = {Gopala Krishna Murthy Nookala and Bharath Kumar Pottumuthu and Nagaraju Orsu and Suresh B. Mudunuri},
  doi       = {10.14569/IJARAI.2013.020508},
  url       = {https://doi.org/10.14569/IJARAI.2013.020508}
}