Text classification is an extensively used phenomenon in natural language processing which has widespread utility in the different domains. Also known as text categorization, text classification finds its usage in various tasks related to information retrieval and management. Spam detection in e-mails, opinion mining or sentiment analysis on social media data, priority e-mail sorting, intent identification from user queries in chatbots, and automated query answering mechanisms are a few examples where text categorization has proved to be highly effective. In earlier chapters, we have discussed various feature selection and dimensionality reduction methods, which are preprocessing steps before text classification. We will briefly discuss supervised learning or classification mechanisms, how a learner is designed, and then we will move on to their implementation in terms of text data. We will also discuss the different cross-validation and evaluation mechanisms...
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You're reading from Mastering Text Mining with R
Ashish Kumar is a seasoned data science professional, a publisher author and a thought leader in the field of data science and machine learning. An IIT Madras graduate and a Young India Fellow, he has around 7 years of experience in implementing and deploying data science and machine learning solutions for challenging industry problems in both hands-on and leadership roles. Natural Language Procession, IoT Analytics, R Shiny product development, Ensemble ML methods etc. are his core areas of expertise. He is fluent in Python and R and teaches a popular ML course at Simplilearn. When not crunching data, Ashish sneaks off to the next hip beach around and enjoys the company of his Kindle. He also trains and mentors data science aspirants and fledgling start-ups.
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Ashish Kumar is a seasoned data science professional, a publisher author and a thought leader in the field of data science and machine learning. An IIT Madras graduate and a Young India Fellow, he has around 7 years of experience in implementing and deploying data science and machine learning solutions for challenging industry problems in both hands-on and leadership roles. Natural Language Procession, IoT Analytics, R Shiny product development, Ensemble ML methods etc. are his core areas of expertise. He is fluent in Python and R and teaches a popular ML course at Simplilearn. When not crunching data, Ashish sneaks off to the next hip beach around and enjoys the company of his Kindle. He also trains and mentors data science aspirants and fledgling start-ups.
Read more about KUMAR ASHISH