Abstract
This is a study paper on the various applications of data mining in stock market. Different methods have been taken into consideration that can solve the problem. Stock market prediction is a complicated task due to its extremely random and unpredicted nature. With a large number of people investing in stocks, it is important that we develop models that can predict their nature. Data mining is used to solve such predictive problems. Various techniques have been discussed, and corresponding models were implemented on the provided data to generate results. The results from all models are compared to give the best fitting model.
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Raghunath, A., Abdul Rajak, A.R. (2021). Applications of Data Mining in Predicting Stock Values. In: Joshi, A., Khosravy, M., Gupta, N. (eds) Machine Learning for Predictive Analysis. Lecture Notes in Networks and Systems, vol 141. Springer, Singapore. https://doi.org/10.1007/978-981-15-7106-0_21
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DOI: https://doi.org/10.1007/978-981-15-7106-0_21
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