Abstract
In this paper, we will evaluate the performance of five machine learning algorithms on large cap ten NIFTY50 companies. Author has implied a 10 year historical dataset that is utilized from yahoo finance and implemented using tensor flow application in google collaborator. Meanwhile, it is very uncertain to refrain from the findings of the concurrent studies to the real–world investing strategies due to lack of predictable results. This paper elaborates the attempt to measure the performance of neural fuzzy inference systems along with five different machine learning algorithms for a 10 year dataset. Several models developed on machine learning concepts were evaluated on a short term dataset that imparted very limited value of prediction accuracy. According to latest research advancement, most researchers focused on in-depth involvement of Machine learning algorithms to elaborate about future stock decisions. The experimental results show that Decision trees algorithm has highest prediction accuracy as compared to other Machine learning Algorithms [8] Neural Fuzzy Inference System.
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Singh, B., Henge, S.K. (2022). Evaluation of Neural Fuzzy Inference System and ML Algorithms for Prediction of Nifty Large Cap Companies Based Stock Values. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A.C., Sari, I.U. (eds) Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation. INFUS 2021. Lecture Notes in Networks and Systems, vol 307. Springer, Cham. https://doi.org/10.1007/978-3-030-85626-7_18
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