Authors :
Ketan Juare; Akanksha Kulkarni
Volume/Issue :
Volume 7 - 2022, Issue 12 - December
Scribd :
https://bit.ly/3EYYQiK
DOI :
https://doi.org/10.5281/zenodo.7698476
Abstract :
Stock market forecasts are a very important
aspect of the financial market. It is important to
successfully predict the stock market in order to get
maximum profit. This document focuses on applying
machine learning algorithms such as Random Forest,
Support Vector Machine, KNN, and Logistic Regression
to datasets. We evaluate the algorithms by determining
performance metrics such as accuracy, recall, precision,
and F-Score. Our goal is to identify the best possible
algorithm to predict the future development of the stock
market. Successful stock market forecasts will have a
very positive effect on stock exchange institutes and
investors.
Keywords :
KNN, Logistic Regression, Machine Learning, Random Forest, Stock Market, Stock Vector Machine Support
Stock market forecasts are a very important
aspect of the financial market. It is important to
successfully predict the stock market in order to get
maximum profit. This document focuses on applying
machine learning algorithms such as Random Forest,
Support Vector Machine, KNN, and Logistic Regression
to datasets. We evaluate the algorithms by determining
performance metrics such as accuracy, recall, precision,
and F-Score. Our goal is to identify the best possible
algorithm to predict the future development of the stock
market. Successful stock market forecasts will have a
very positive effect on stock exchange institutes and
investors.
Keywords :
KNN, Logistic Regression, Machine Learning, Random Forest, Stock Market, Stock Vector Machine Support
