A comprehensive study on machine learning concepts for text mining

Abstract

The aim of machine learning is to solve a given problem using past experience or example data. Many machine learning applications are using now-a-days already. More aspiring problems can be handled as more data become accessible. Here. in this context we learn in detail about text mining as a multi-dimensional field which involves the closely linked areas or sections like 1. Retrieving information, 2. Machine learning concepts shortly termed as ML, 3. Statistics, 4. And finally Computational linguistics and specifically to be mentioned, data mining. With the use of sample data or previously gained experience, machine learning is included into computers to enhance or improve a performance decisive factor. In this context we have detailed a model up to some level of constraints, and learning is the processing of a main content to enhance the parameter of the form using the training or sample data or previously gained experience. This may be designed to gain knowledge from the given data, or use the effect for changes in the future, or both. These learning techniques also helps us to make solutions to various bugs which includes vision, speech recognition, and robotics. We take the example of the main analysis of preprocessing of tasks and procedures, then classification, then clustering, information extraction and finally visualization.