Effective Multicategory Classification Using ELM-ANP Approach for Microarray Gene Expression Cancer Diagnosis
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Abstract
Cancer is one of the fearful diseases found in majority of the living organism, which is one of the demanding focuses for scientist towards 20th century. There were bunch of proposal from a variety of establishers and detailed picture examination was still under processing. The main aim of microarrays is hybridization between two DNA strands, the property of balancing nucleic acid series to particularly pair with each other by forming hydrogen bonds between complementary nucleotide base pairs. This paper presents a fast and efficient classification technique called the Fast ELM algorithm is used for a multicategory cancer diagnosis problem according to the microarray data is supplied. ELM provides significant classification results compared to other classifiers because of its unique features. Moreover, the drawbacks of ELM are effectively dealt by using ELM as classifier. When the dataset is large, the usage of ELM will take more time for execution. For this purpose, this approach uses Levenberg Marquadt algorithm for training which speeds up the training process. In this paper, ELM is integrated with the ANP approach for finding the weighted matrix. This would enhance the performance of the overall system.
Keywords: Cancer, DNA Microarray , ELM, Classifier, Levenberg Marquadt algorithm, ANP.
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