LATEST NEWS CLASSIFIER Introduction: Nowadays large amount of information is available in electronic format. So with these data it is necessary to classify and analyse such data and facts which would help in decision making. This is possible because of data mining which is useful in extracting data from huge databases and here it is used to classify the type of news in a given newspaper or article. It is quite challenging as it requires more of pre-processing to convert the unstructured data to some structured information. The categorization/classification of the news benefits the user to access the news of their interest as the number of news increase the difficulty also increases. In this paper the news are been classified based on their content and headlines in a particular article or newspaper.
-->Steps involved :
- News collection
- News Pre-processing
- Indexing
- Feature extraction
- Classification
-->Models used: Decision Tree Random forest decision tree Multinomial naive bayes Naive bayes SVC