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Real time decision making forecasting using data mining and decision tree

机译:使用数据挖掘和决策树的实时决策预测

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摘要

The stock market is gaining relevance with each day. Much research has been done in the area of finding a means to forecasting the fluctuations. Yet decision-making remains a challenging task in the current age of forecasting. Our proposed algorithm uses autoregressive methods to assist with the decision to buy as well as the selling point for any stock price. The proposed algorithm is more useful for the shareholder than the trader. This decision making tool can be essential to the formation of the business plan and its viability is proved by the significant amount of profit that has already been yielded.
机译:股市正在与每一天获得相关性。 在找到预测波动的手段的领域已经完成了许多研究。 然而,决策仍然是目前预测年龄的具有挑战性的任务。 我们所提出的算法使用自动增加方法来协助决定购买以及任何股票价格的卖点。 该算法对股东而不是交易者更有用。 该决策工具对于业务计划的形成至关重要,并且其可行性被已经产生的大量利润证明。

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