Cancer Classification Based on Jumping Emerging Pattern Mining Algorithm

doi:10.3969/j.issn.1006-2475.2018.05.020

Abstract

Abstract: Classification is an important topic in data mining, but currently, the classification of cancer data is still relatively small. In recent years, Strong Jumping Emerging Patterns (SJEP) is a new model with strong ability to distinguish, which has obvious advantages for the classification of cancer data. In order to further improve the classification accuracy of cancer data, this paper introduces the idea of integrated learning, and makes some improvements to the original Boosting algorithm. The improved Boosting algorithm is combined with SP-tree classification algorithm, an SP_Boost algorithm based on SP-tree classification algorithm is proposed.

Key words: classification algorithms, strong jumping emerging patterns, ensemble learning

CLC Number:

TP301

QIAO Yuan, LIAO Xiao-ping, SHAO Kai-xia. Cancer Classification Based on Jumping Emerging Pattern Mining Algorithm[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2018.05.020.

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