Paquete Support Vector Frontier
Project description
SVF Package
Support Vector Frontiers package
Support Vector Frontier (see Valero-Carreras et al., 2022) (SVF) is a machine learning technique, based on Support Vector Machines (SVM), used for the estimation of production functions.
Contents
- Different types of SVF:
- Complete Support Vector Frontiers (SVFC):
- Simplified Support Vector Frontier (SSVF):
- Simplified Support Vector Frontier Dual (SVF dual):
- Support Vector Frontier Splines (SVF-SP):
- Cross Validation:
- k-folds:
- Train test split:
- Calculation of inefficiencies:
- FDH, DEA, SVF, CSVF:
- BCC input orientation:
- BCC output orientation:
- Weighted aditive:
- Directional distance:
- Russell Input Orientation:
- Rusell Output Orientation:
- Enhanced Russell Orientation:
- FDH, DEA, SVF, CSVF:
Instalation
For installing the package you can use the command:
pip install SVF_Package
SVF Package uses different packages for correct execution:
- Pandas
- Docplex
- Numpy
- Scikit-learn
Warning
SVF is an algorithm with a high computational cost. The performance of the algorithm largely depends on the amount of inputs and sample size.
The code has been tested for a ...
Examples
Contact
Daniel Valero Carreras: email
University Miguel Hernández (Elche)
Institute Center of Operations Research (CIO)
Bugs can be reported to github repository. The code can also be found there.
License
MIT License
Copyright (c) 2022- DANIEL VALERO CARRERAS
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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