IRJET- Information Reterival of Text-based Deep Stock Prediction

This document discusses using machine learning techniques like decision trees to predict stock market performance based on past stock data. It specifically focuses on using decision tree classifiers to build predictive models using historical data from two major companies on the National Stock Exchange in India. The goal is to analyze patterns in the past stock data to predict future stock prices and trends. It evaluates the effectiveness of different decision tree algorithms based on their accuracy and speed in constructing predictive trees from the training data. The authors conclude various data mining methods can be effectively applied to financial data for stock prediction and improving investment outcomes.