International Journal of Research and Development in Engineering Sciences https://www.ijrdes.com K. Kantha Raju 2 6 (November - December) 2020 11 November-December enText miningClassificationData miningMachine learningDocument analysis Text mining a crucial field within data mining focuses on extracting meaningful patterns trends and knowledge from unstructured textual data With the exponential growth of digital content effective classification techniques have become essential for organizing and interpreting large text datasets This paper reviews various data mining classification techniques applied in text mining including Decision Trees Nave Bayes Support Vector Machines SVM KNearest Neighbor KNN and Neural Networks Each method offers unique strengths in handling highdimensional text data and improving the accuracy of document categorization sentiment analysis and topic detection The study examines the comparative performance of these algorithms based on factors such as precision recall computational efficiency and adaptability to largescale datasets Additionally it discusses recent advancements in hybrid and ensemble models that combine multiple classifiers to enhance predictive performance The review concludes that the selection of an appropriate classification technique largely depends on the nature of the text data feature representation methods and the specific application domain Copyright (c) 2026 International Journal of Research and Development in Engineering Sciences. All rights reserved. 2020 All Rights Reserved