This is a simple node app that accepts a companies salary data, i.e., a .csv file that has designations, salaries for those designations and a certain preordered level assigned with each designation depending upon the salary (higher the salary, higher the level). Besides this, the app also demands two inputs:

• The level at which the employee was in the company (a fractional number between 1 and total number of designations) where the fractional part arises by virtue of years of experience. For instance, if I am working as a Senior Executive which is level number 6 with 3 years of experience, then if in my company promotions occur after an average of 6 years of continuing the same post, then my level becomes 6.5

• The salary which the employee, while negotiations, claims to have had in the previous company.

The node app.js file then sends the information to a python script that implements Random Forest Regression , an ensemble Machine Learning Algorithm on the data to predict the possible salary of the employee.

The app then reports whether:

• The employee is honest, i.e., told his exact salary
• The employee understated his salary
• The employee was trying to bluff the company, claiming more than he deserves. The app also gives the %Bluff of the employee

node
python 3.6 or later

• clone this Delusion-Detector on your local machine
• Change the path to Python as per your machine in the options variable in app.js
• cd Delusion-Detector
• npm install
• node app.js
• Open your favorite browser and go to localhost:3000
• Enter any .csv file that follows the aforementioned details(SampleData has two .csv files for reference )
• Enter any level and Claimed Salary
• The Output will be shown besides a Random Forest Regression Plot that will be saved in plotPics for trend analysis!