A set of some ML utils frequently used by me while working as Data Scientist in Cognizant
These instructions will get you a copy of the library up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
You need Python 3.x.x for sure, and following libraries
- scikit-learn
- pandas
- matplotlib
- seaborn
Follwoing step by step commands will tell you how to get a library running
- Firstly install the prerequisites
pip install -r requirements.txt
- Now build the wheel package
python setup.py sdist bdist_wheel
- This command should output a lot of text and once completed should generate two files in the dist directory:
dist/
cognilearn_adityajain-0.0.3-py3-none-any.whl
cognilearn_adityajain-0.0.3.tar.gz
- Go to dist directory and install package using following command
pip install cognilearn_adityajain-0.0.3-py3-none-any.whl
Currently package contains following features. More will be added soon
-
In cognilearn.metrics
- sensitivity
- specificity
- accuracy
- roc_curves
- specificity_vs_sensitivity
- confusion_matrix_modified
-
In cognilearn.feature_selection
- backward_selection
- forward_selection
-
In cognilearn.analysis
- decile_analysis
- information_value
- prepareDeciles
-
In cognilearn.preprocessing
- correlation_graph
-
In cognilearn.ensemble
- Stacker
Please feel free to contribute to the library. If you have something which can ease the work of data scientist around the world, just fork repository and give a pull request or directly contact me and provide code snippet. I would love to put your name in contributors.
Current version is 0.0.3. We will release new version every month.
- Aditya Jain - Portfolio
See also the list of contributors who participated in this project.
This project is licensed under the GNU General Public License v3.0 - see the LICENSE.md file for details
- Keshav Kumar
- Cognizant Data Science Team