/ai-job-title-level-classification

Primary LanguagePython

Classification of job positions by level

This is a project to classify job positions using machine learning, more specifically, supervised learning. The main goal is to get a classifier that receives a job position in the form of a sentence, written in natural language, for example CEO and Founder and returns the job level for that position. The different levels (labels for the classification) are:

  • C-Suite
  • VP
  • Director
  • Manager
  • Other

In the example, CEO and Founder would return C-Suite.

There is an analogous project but it classifies according to the area of the position: Classification of job positions by area. If you use pip and virtual environments, you can install easily the named library: $pip install -r requirements.txt.

Content

You can see the explanation in the area classifier documentation.

Script execution

The steps are the same as the classification by level:

  1. Run data_process/tsv_file_to_dataframe.py to extract the data from the tsv file and split the dataset.
  2. Run <clf name>_fit_tune_classifier.py to fit and tune the classifier. fit is to learn and fit the model to the train set. tune is to search for the optimal combination of the hyperparams, the ones that achieves better results (tuning may take a while).
  3. Run <clf name>_test_classifier.py to test the trained classifiers and show the results. Besides, a classified example set is stored in test_data/<clf name>_results.tsv.

Note: <clf name> can be mlp or sgd, depending on the classifier.

Results

These are the results of each classifier:

MLP

                precision    recall  f1-score   support

     C-Suite       0.90      0.93      0.92        29
    Director       0.97      0.92      0.94        37
     Manager       0.90      0.95      0.92        19
       Other       0.93      0.95      0.94        41
          VP       1.00      0.96      0.98        24

    accuracy                           0.94       150
   macro avg       0.94      0.94      0.94       150
weighted avg       0.94      0.94      0.94       150

SGD

                precision    recall  f1-score   support

     C-Suite       0.97      0.97      0.97        29
    Director       0.97      0.92      0.94        37
     Manager       1.00      1.00      1.00        19
       Other       0.95      1.00      0.98        41
          VP       1.00      1.00      1.00        24

    accuracy                           0.97       150
   macro avg       0.98      0.98      0.98       150
weighted avg       0.97      0.97      0.97       150