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Research Paper | Computer Science & Engineering | India | Volume 8 Issue 4, April 2019 | Rating: 6.8 / 10
Predictive Modelling Using Random Forest Classifier and Decision Tree Algorithm
Subhojit Paul, Ankan Paul, Sahil Sakar, Tuhin Sarkar, Debdoot Ganguly, Siddhartha Sen, Soumik Dutta
Abstract: In the 21stcentury with the development of programming languages new dimensions are opening in the line of work which are improving the quality of life and also making it simpler and better. Cricket has a great influence on the people of this country and is almost considered as a religion. With the introduction of Indian Premier League the excitement of people has reached new heights. People often debate which team will win the upcoming match and the championship. The main focus of our program is to predict the winner of the upcoming matches using Random Forest Regression method. The dataset is fed with the names of the teams and the team which won the toss and the winner. Based on this data we predict which team may win the next match. Random Forest Regression being a supervised learning algorithm helps in accurate and stable prediction and as such is very helpful in gaining the desired result.
Keywords: Machine Learning, Random Forest Regression
Edition: Volume 8 Issue 4, April 2019,
Pages: 1202 - 1203