Dr. SANTOSH KUMAR BYRABOINA 06 02 To illustrate the procedures we use a sample of US students answers to problemsolving questions on the 2022 PISA N 426 Classifier development operations are carried out utilizing the shown methods after the creation and selection of concrete features All of the methods yielded good results in terms of categorization accuracy Recommendations for choosing classifiers are provided taking into account research topics classifier interpretability and classifier simplicity Both supervised and unsupervised learning approaches provide outcomes that are explainedWith the advent of big data it has become more difficult to glean insights from large datasets This study aims to provide light on the possible benefits drawbacks and ramifications of using advanced analytical techniques to extract significant patterns correlations and trends from large datasets by examining the overlap between data mining and big dataThe fundamental goals of this research are to determine the most effective data mining methods for largescale data analysis evaluate their scalability and computing efficiency and get a knowledge of their potential to uncover previously unknown insights In order to better understand the interplay between data mining approaches and the complexities of big data this study will analyze the relevant literature and perform experiments With the advent of the age of big data there has been an unprecedented flood of data in many fields requiring novel methods to be developed in order to glean useful insights Knowledge discovery relies heavily on data mining which has developed to meet the problems provided by big datas volume velocity and diversity Copyright (c) World Journal of Pharmaceutical Seiences. All rights reserved 2026