Open AccessCrypto Currency Market Price Prediction Using Data Science Process
Author(s) -
Karthik Vikram,
Nikhil Sivaraman,
P. Balamurugan
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40521
Subject(s) - cryptocurrency , random forest , computer science , digital currency , artificial intelligence , decision tree , machine learning , lasso (programming language) , currency , logistic regression , econometrics , data mining , economics , payment , computer security , world wide web , monetary economics
Cryptocurrency is commonly called as digital currency where the coin ownership records are stored in an electronic ledger existing in a form of a computerized database using strong cryptography approach which is used to maintain the creation and updation of an addition coin in a market, it is also used to check and maintain the current ownerships of the coins. Nowadays cryptocurrency is used in largescale and there is a sudden rise or decrease in their share and it is difficult to predict the price of the crypto currency. In this project a machine learning model is built to predict the price of crypto currency. The application of data science process is applied for getting the better model for predicting the outcome. Variable identification and data understanding is the main process in building the successful model. Different machine learning algorithms are applied on the pre-processed data and the accuracy are compared to see which algorithm performed better other performance metrics like precision, recall, scores are also taken in consideration for evaluating the model. The machine learning model is used to predict the crypto currency outcome Keywords: crypto currency, Decision Tree, Prediction, Random Forest, Logistic regression, Linear Regression, LASSO Regression, Ridge Regression.