Text classifier

The purpose of this program is to classify text in python progrmming language using three following methods:

• Naive Bayes classifier
• Decision Tree
• KNN Procedure of this software consist of the below phases of word processing:

Preprocessing

In this part, different operation like:

• tokenizing
• deleting punctuations
• removing stop words
• stemming would be performed on the input texts.

Feature generation

Using N-grams (Unigram, Bigram and Trigram) methodologies to produce features vactor.

Weighting features

In order to weigh feature we implement TF-IDF concepts which make it easier for accurate classification in further processing.

Evaluating the results

In the final stage the software would evaluate classifier using N-Gram model and result for three important criterion would be calculated which are:

• Precision
• Recall
• F1-Score