Published Paper Details:

Nowadays, the prediction of share market prices and conditions has become a major researched topic amongst the data scientists, investment bankers, and stock brokers. As, the behavior of share market is very nonlinear and volatile in nature, it makes a very high-risk investment. Consequently, a lot of researchers have came up with their efforts to forecast the share market and average movement. Researchers have used various methods in computer science and economics in their illustrate to gain a piece of this volatile information and make great fortune out of the share market investment. The approaches like data mining and machine learning approaches can incorporate into Business Intelligence (BI) systems to help users for decision support in many real-life applications. This paper presents the brief survey of application of machine learning in share market prediction and investigates various techniques for the share market prediction using like Artificial Neural Network (ANN) and Support Vector Machine (SVM). ANN is non- linear and non- parametric classifier which is viable for forecasting of share prices. Support Vector Machine focuses on marginal values rather than average values for the classification predicting model. The aim of this paper is to provide a review of the application of machine learning in share market prediction to determine what can be done in the future.