Our top 2 solution to RuCode 2022 AI Payroll task

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Our team:

• Our task was to predict the salary for given vacanvies from trudvsem.ru
  
• The data was given as a .csv file with approx. 1kk samples in train.csv (71 columns) and 40k samples in test.csv (68 columns) (public - 40%, private - 60%)
  
• The training data included categorical, binary, continous and text features
  
• The target variable was mean_salary and additional targets were base_salary_max and base_salary_mean
  
• Many of the values were missed, e.g. in one of the features 95% were nan values
  

1. Fill in the misssing values
2. Generate new features
3. Select features
4. Target Transformation
5. Cross validate model
6. Stabilize the model