Fake-job-ads

This dataset contains 18K job descriptions out of which about 800 are fake. The goal is to define the text as a real or fake job posting.

Thise date was be used to create classification models like:

• Naive Bayes classifier,
• Random forest,
• Logistic regression.

Data was unbalanced. To decieding this problem was used Resampling Techniques:

1. Oversample minority class;
2. Undersample majority class.

First technique got the best result with accuracy score 99% for Random Forest model. Trained Random Forest model was used for prediction on new random data. Random job ads from Duunitori.fi and Monster.fi sites were taken as an example.