Problem Statement
Hello everyone here the detection of fake reviews out of a massive collection of reviews having various distinct categories like the dataset used having reviews of Home and Office, Sports, etc. so with each review having a corresponding rating, label i.e. CG(Computer Generated Review) and OR(Original Review generated by humans) and the review text. Here main task is to detect whether a given review is fraudulent or not. If it is computer generated, it is considered fake otherwise not. Description: The generated fake reviews dataset, containing 20k fake reviews and 20k real product reviews.
OR = Original reviews (presumably human created and authentic);
CG = Computer-generated fake reviews.
Machine Learning Algorithms Used here are as follows
1.Logistic Regression
2.K Nearest Neighbors
3.Support Vector Classifier
4.Decision Tree Classifier
5.Random Forests Classifier
6.Multinomial Naive Bayes