Explainable Deep Convolutional Candlestick Learner
National Taiwan University（台湾大学）；Soochow University（东吴大学）
英文摘要：
Candlesticks are graphical representations of price movements for a given period. The traders can discovery the trend of the asset by looking at the candlestick patterns. Although deep convolutional neural networks have achieved great success for recognizing the candlestick patterns, their reasoning hides inside a black box. The traders cannot make sure what the model has learned. In this contribution, we provide a framework which is to explain the reasoning of the learned model determining the specific candlestick patterns of time series. Based on the local search adversarial attacks, we show that the learned model perceives the pattern of the candlesticks in a way similar to the human trader.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
