Stock market prediction is a very important aspect in the financial market. It is important to predict the stock market successfully in order to achieve maximum profit. This paper will focus on applying machine learning algorithms like Random Forest, Support Vector Machine, KNN and Logistic Regression on datasets. We evaluate the algorithms by finding performance metrics like accuracy, recall, precision and fscore. Our objective is to identify the best possible algorithm for predicting future stock market performances. The successful prediction of the stock market will have a very positive impact on the stock market institutions and the investors also.

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