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classifier.py
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classifier.py
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"""
Implementation of a 1-nearest neighbor classifier.
Giancarlo Paoletti
Copyright 2021 Giancarlo Paoletti ([email protected])
Please, email me if you have any question.
Disclaimer:
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, PAVIS or IIT 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.
LICENSE:
This project is licensed under the terms of the MIT license.
This project incorporates material from the projects listed below
(collectively, "Third Party Code").
This Third Party Code is licensed to you under their original license terms.
We reserves all other rights not expressly granted, whether by implication,
estoppel or otherwise.
Copyright (c) 2021 Giancarlo Paoletti, Jacopo Cavazza, Cigdem Beyan and
Alessio Del Bue
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.
References
[1] Giancarlo Paoletti, Jacopo Cavazza, Cigdem Beyan and Alessio Del Bue (2021).
Unsupervised Human Action Recognition with Skeletal Graph Laplacian and Self-Supervised Viewpoints Invariance
British Machine Vision Conference (BMVC).
"""
def knn_classification(knn, features, labels, step='train'):
if step == 'train':
return knn.fit(features, labels)
elif step == 'test':
return knn.score(features, labels)