Implementation Of Convolutional Neural Network Method For Classification Of Baum Test

Setiawan, Irvan; Yusnitasari, Tristyanti; Nurhady, Hafizh; Hizviani, Noor Vika

doi:10.1109/icic50835.2020.9288595

Cited by 4 publications

(1 citation statement)

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“…The x-and y-axes represent the date and the actual BTC price for that date, respectively. The ratio of the training data to the test data was set to 7:3, which is a commonly used ratio [40], [41], [42]. Among the total data, data for 1,037 days from April 21, 2018, to February 20, 2021, were used as training data.…”

Section: ) Data Collectionmentioning

confidence: 99%

Twitter Sentiment Analysis-Based Adjustment of Cryptocurrency Action Recommendation Model for Profit Maximization

Park

Seo

2023

IEEE Access

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Cryptocurrencies have recently attracted considerable attention, resulting in research mainly on deep learning-based price prediction models to maximize profit. Two research approaches have been adopted. Studies adopting the first approach directly predict the future cryptocurrency price. Long short-term memory (LSTM) and gated recurrent unit (GRU), which show high performance in time-series data, are mainly used for this approach. Further, studies adopting the second approach recommend actions to investors to maximize profits, such as ''Sell'', ''Buy'', and ''Wait.'' In this approach, classification models are used and results are derived based on probabilities. However, these action recommendation models do not consider the quality of the result. For example, it is risky to accept the result when the probability that the result of the action recommendation model for two classes is the correct answer is approximately 51%. To solve this problem, we recommend a method for adjusting the result of the action recommendation model based on Twitter sentiment analysis. The experimental results show that the proposed adjustment method improves the performance by approximately 3% compared to the conventional methods and are statistically validated.

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Section: ) Data Collectionmentioning

confidence: 99%