GitHub / IDB-FOR-DATASCIENCE / Predicting-fit-of-a-candidate-for-a-job-using-tree-based-models
We use multiple Tree boosting models and compare their performance to calculate the fit percentage of a candidate for the job they apply for. Also try to handle categorical methods using various methods.
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Language: Jupyter Notebook
Size: 972 KB
Dependencies parsed at: Pending
Created at: about 4 years ago
Updated at: about 4 years ago
Pushed at: about 4 years ago
Last synced at: about 2 years ago
Topics: catboost, hyperopt, lightgbm, onehot-encoding, targetencoding, xgboost