Term Frequency (TF) and Inverse Document Frequency(IDF) are the two terms which is commonly observe in Natural Language Processing techniques. It is used to find the word occurences and their contribution or impact or rather we can say importance in any given sentence of a document. This techniques are more often used in sentiment classification . The retrival of information in the form of emotions from the given word is more easier when a machine knows the significance of a word. The classification of positive and negative messages conveyed from any given sentence is generally taken care of by the above techniques. We will be following few steps in order to understand the concept in a better ways.

Suppose we are given a huge document given below which has many sentences and want to perform text classification and conclude using the TF and IDF techniques that what is the emotion or message that is conveyed through the below sentences.

Today morning the teams began their practice session. The boys Kabaddi team has gone through 1 round of practice. The boys football team has started practice.The boys cricket team has been doing the practice. The girls volleyball team is ready.The boys relay race team is up .

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