Treffer: Cryptocurrency Price Prediction by Integrating Optimization Mechanism to Machine Learning.

Research is being done right now to try to predict the future value of cryptocurrency. The possibility of using a python-based approach has been explored by the scientific community as a means of realizing this aim. In predictive analytics, it is becoming standard practice to use the same dataset for both training and testing purposes. Traditional studies have been slowed down by problems with precision and efficiency. This research makes use of optimization and the Python programming language to provide a versatile prediction model with little implementation time. Dataset size is decreased when classification is performed in Python, which shortens the training period. Eliminating extraneous information also improves the performance of the trained model. Because of this change, we want to develop a system that is both adaptable and extensible. To put it another way, such a system would help cryptocurrency investors make better decisions while buying and selling cryptocurrency. Using several factors, the study's results have significantly influenced Bitcoin price forecasts. Investment choices are often guided by such analyses for many fund managers and private investors. Scientists have developed a flexible and scalable strategy for determining an appropriate script's ideal value. Investors will need a mechanism to choose which currency to purchase at any given moment according to market circumstances as trading platforms progress. [ABSTRACT FROM AUTHOR]

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