News-article-classification

News Article Classification Model is a machine learning model that classifies news articles into various categories - business, tech, politics, sports and entertainment using Natural Language Processing (NLP).

Models

The models used are:-

• Logistic Regression
• Random Forest
• Multinomial Naive Bayes
• Support Vector Classifier
• Decision Tree Classifier
• K Nearest Neighbour
• Gaussian Naive Bayes.

Python Libraries

Download these libraries using pip if haven't already:-

• Natural Language Toolkit
• Regular Expressions
• Numpy
• Pandas
• Matplotlib
• Wordcloud
• Scikit-Learn

Dataset

• The dataset News.csv comprises of 1490 news articles.
• It contains three columns - ArticleId, Text and Category(business/tech/politics/sports/entertainment).
• 30% of dataset is split for test set and the remaining is used for training.

Data Visualization in Numeric form:-

Data Visualization in Percentage form:-

Visualizing Category Related Words:-

Business Related Words:-

Tech Related Words:-

Politics Related Words:-

Sports Related Words:-

Entertainment Related Words:-

Data Pre-processing

• Removal of tags.
• Removal of special characters.
• Conversion to lower case.
• Removal of stop-words.
• Lemmatizing the Words

Accuracy

• Accuracy, Precision, Recall and F1 score is displayed for each model.

• The best accuracy of model is 97.99 from Random Forest.