HIERARICAL CLUSTER BASED DATA PREPROCESSING FOR STOCK MARKET DATA PREDICTION

Abstract

Financial area analysis are not limited to enterprise performance analysis. It merits examining as wide an area as conceivable
to get the full impression of a particular enterprise. Stock market dataset content is a datum source that offers the prediction
data of the ups and downs of growth in stock market, trading tasks, daily and timely status, and so on. Consequently, it merits
investigating the news entry of up to date data. Mining the data and forecasting the data will be a challenging task due to huge
volume of data , and doesn't give high precision. To beat this shortcoming, another equal data pre-processing algorithm in
view of Hierarchical Clustering is proposed in this paper. This algorithm can decrease the size of information and runtime.
This research using the proposed model will provide the best solution. The examination demonstrates the performance of our
proposed preprocessing algorithm is better than existing