Probabilistic Determination of Class for an Unbalanced Dataset (International Journal of Engineering and Computer Science, 2018)
Poker is one of the world’s most popular and widely played card games. In Poker, there is a fixed set of winning conditions and the player with the highest winning condition wins the game. The main part of the game is to bet strategically and in a calculated manner so that there is less chance of risk and the opponents are not able to guess the cards in the hand. To help players understand when and how to bet smartly, this application will be developed. This system provides knowledge to the users about their probability of winning based on the cards available to them. The system which has been developed is lightweight and easy-to-use so that all types of players can use it. The aim of this system is to help gamblers bet better thereby increasing their winnings, addiction to Poker gambling and also generate greater revenue collections for gaming consortiums.. The most important point of this paper is to show how we have used data mining and statistical probabilities to formulate an algorithm which gives out correct predictions of the winning hand. We formally define the system and outline the challenges that arose while developing technology to support it. We hope that this paper will encourage more research by the gaming consortiums and the gambling community in this exciting area of winning by probability calculations and card counting.