To Detect Irregular Trade Behaviors In Stock Market By Using Graph Based Ranking Methods [article]

Loc Tran, Linh Tran
2019 arXiv   pre-print
To detect the irregular trade behaviors in the stock market is the important problem in machine learning field. These irregular trade behaviors are obviously illegal. To detect these irregular trade behaviors in the stock market, data scientists normally employ the supervised learning techniques. In this paper, we employ the three graph Laplacian based semi-supervised ranking methods to solve the irregular trade behavior detection problem. Experimental results show that that the un-normalized
more » ... d symmetric normalized graph Laplacian based semi-supervised ranking methods outperform the random walk Laplacian based semi-supervised ranking method.
arXiv:1909.08964v1 fatcat:vndbp53msnadfmki7723vxtllm