English: Exponential growth of data in recent time is a very critical and challenging issue which requires significant attention. More than two third available information is stored in unstructured format largely in text formats. Knowledge can be extracted from many different available sources. Data which are mainly in unstructured format remain the largest readily available source of knowledge either online or offline so it must be attended very carefully. Text mining is believed to have a very high commercial potential value. Text classification is the process of classifying the text documents according to predefined categories. There are many databases which are dynamic and getting updated during course of time. To handle and classify these kind of datasets incremental learning is required which train the algorithm as per the arrival of new data. This paper covers different machine learning algorithms for text classification on the dynamic or incremental database also includes classifier architecture and Text Classification applications.