Volume - 13 | Issue-1
Volume - 13 | Issue-1
Volume - 13 | Issue-1
Volume - 13 | Issue-1
Volume - 13 | Issue-1
Aim: The main aim of the research work is to predict the stock equity using the Linear Regression (LR) over the Random Forest (RFA). Materials and Methods: The two algorithms linear regression and random forest are compared with a sample size = 10. Sample size is calculated using G power software and determined as 10 per group with pretest power 80%, threshold 0.05% and CI 95%. Results: The analysis of the results shows that the Linear Regression has a high accuracy of (89.36%) in comparison with Random Forest(87.58%). The P value achieved is 0.620 (p>0.05), which shows it is a statistically insignificant difference between the study groups. Conclusion: Prediction in classifying from the results it is concluded that the proposed algorithm Linear Regression will produce better results than the Random forest algorithm.