Published May 19, 2015 | Version v1
Software Open

CostSensitiveClassification Library in Python

Authors/Creators

  • 1. University of Luxembourg

Description

CostCla is a Python open source cost-sensitive classification library built on top of Scikit-learn, Pandas and Numpy. CostCla provides a wide range of state-of-the-art example-dependent cost-sensitive methods for binary classification tasks. Source code, binaries and documentation are distributed under 3-Clause BSD license in the website https://github.com/albahnsen/CostSensitiveClassification.

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CostSensitiveClassification-master.zip

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Additional details

References

  • Correa Bahnsen, A., Stojanovic, A. Aouada, D., & Ottersten, B. “Improving Credit Card Fraud Detection with Calibrated Probabilities”, in Proceedings of the fourteenth SIAM International Conference on Data Mining, 677-685, 2014.
  • Correa Bahnsen, A., Aouada, D., & Ottersten, B. “Example-Dependent Cost-Sensitive Logistic Regression for Credit Scoring”, in Proceedings of the International Conference on Machine Learning and Applications, 2014.
  • Correa Bahnsen, A., Aouada, D., & Ottersten, B. “Example-Dependent Cost-Sensitive Decision Trees. Expert Systems with Applications”, Expert Systems with Applications, in press, 2015, http://doi.org/10.1016/j.eswa.2015.04.042
  • Correa Bahnsen, A., Aouada, D., & Ottersten, B. “Ensemble of Example-Dependent Cost-Sensitive Decision Trees”, 2015, http://arxiv.org/abs/1505.04637.