scholarly journals Price Trend Prediction of Stock Market Using Outlier Data Mining Algorithm

2021 ◽  
Vol 6 (4) ◽  
pp. 8-11
Author(s):  
Shubham Nipane ◽  
Prashant Kale ◽  
Payal Kapsekar ◽  
Pooja Agrawal ◽  
Omkar Dudbhure
Keyword(s):  
Data Mining ◽  
Stock Market ◽  
Data Mining Algorithm ◽  
Trend Prediction ◽  
Price Trend ◽  
Mining Algorithm ◽  
Outlier Data

Design of data mining algorithm based on rough entropy for us stock market abnormality

2020 ◽  
Vol 39 (4) ◽  
pp. 5213-5221 ◽  
Author(s):  
Guangtong Wang ◽  
Jianchun Miao
Keyword(s):  
Data Mining ◽  
Time Series ◽  
Stock Market ◽  
Global Economy ◽  
Data Mining Algorithm ◽  
Market Anomalies ◽  
Mining Algorithm ◽  
The Us ◽  
Stock Market Anomalies ◽  
Market Anomaly

The economic interaction between the countries of the world is gradually strengthening. Among them, the US stock market is a “barometer” of the global economy, which has a huge impact on the global economy. Therefore, it is of great significance to study the data in the US stock market, especially the data mining algorithm of abnormal data. At present, although data mining technology has achieved many research results in the financial field, it has not formed a good research system for time series data in stock market anomalies. According to the actual performance and data characteristics of the stock market anomaly, this paper uses data mining techniques to find the abnormal data in the stock market data, and uses the isolated point detection method based on density and distance to analyze the obtained abnormal data to obtain its implicit useful information. However, due to the defects of traditional data mining algorithms in dealing with stock market anomalies containing uncertain factors, that is, the errors caused by other human factors, this paper introduces the roughening entropy of the uncertainty data and applies its theory to the field of data mining, a data mining algorithm based on rough entropy in the US stock market anomaly is designed. Finally, the empirical analysis of the algorithm is carried out. The experimental results show that the data mining algorithm based on rough entropy proposed in this paper can effectively detect the abnormal fluctuation of time series in the stock market.

scholarly journals A product-centric data mining algorithm for targeted promotions

2020 ◽  
Vol 54 ◽  
pp. 101940 ◽  
Author(s):  
Raymond Moodley ◽  
Francisco Chiclana ◽  
Fabio Caraffini ◽  
Jenny Carter
Keyword(s):  
Data Mining ◽  
Data Mining Algorithm ◽  
Mining Algorithm
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