Prediction of Identical Twins Using Naive Bayes Algorithm Compared with Random Forest Based on Biometrics

The purpose of the research labour is to classify the prediction of identical twins based on biometrics like fingerprints using naïve bayes algorithm. The Simplification is performed is performed utilising a n = 10 sample size in Naive Bayes Algorithm and Random Forest with sample size is 10 with n. The analysis of the result shows that in compared with Random Forest(92.25) has highest accuracy in compared with Naive Bayes(91.01). There is a sizable distinction between the study group. Prediction in analysing the identical twins Random Forest(92.25) appears to produce 1.25% more accurate results than the Naive Bayes(91.01).