摘要：The main objective of this paper is improving the BOAT classification algorithm and applying it in credit card big data analysis. Decision tree algorithm is a data analysis method for the classification which can be used to describe the extract important data class models or predict future data trends. The BOAT algorithm can reduce the data during reading and writing the operations, the improved algorithms in large data sets under the operating efficiency, and in line with the popular big data analysis. Through this paper, BOAT algorithm can further improve the performance of the algorithm and the distributed data sources under the performance. In this paper, large banking sectors of credit card data as the being tested data sets. The improved algorithm, the original BOAT algorithms, and the performance of other classical classification algorithms will be compared and analyzed.
