• Abhishek
• Dr. Dinesh Kumar

Data mining problems that are concerned with prediction fall under the category of classification. Its primary responsibility is to categories the data to derive predictions about future data. The act or process of classifying anything might be thought of as classification in general. Building models that predict an object's class based on its features is one of the most prevalent tasks in data mining.The classification algorithms Naive Bayes, Meta Classifiers and Decision Tree Based Classifiers have all been compared in this research. To assess the effectiveness of several categorization algorithms, an experiment has been put up. Theoretical study and experimental findings demonstrate that the "Classification by Regression" method successfully identified all examples, while "Decision Tree based Classifiers" produced the fewest errors and "Nave Bayes" classified all instances in the shortest amount of time.

Naïve Bayes, Datasets, Classification, Meta Classifiers, Naïve Bayes, Decision Tree.

"A Comparative Analysis of Different Data Mining Models: Decision Tree, Meta and Naïve Bayes", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 8, page no.a634-a638, August-2022, Available :http://www.jetir.org/papers/JETIR2208078.pdf

"A Comparative Analysis of Different Data Mining Models: Decision Tree, Meta and Naïve Bayes", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 8, page no. ppa634-a638, August-2022, Available at : http://www.jetir.org/papers/JETIR2208078.pdf