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* feat: created kivy gui boilerplate * migrated docker base image to debian Signed-off-by: ltcptgeneral <learthurgo@gmail.com> * migrated to ubuntu Signed-off-by: ltcptgeneral <learthurgo@gmail.com> * fixed issues Signed-off-by: ltcptgeneral <learthurgo@gmail.com> * fix: docker build? * fix: use ubuntu bionic * fix: get kivy installed * @ltcptgeneral can't spell * optim dockerfile for not installing unused packages * install basic stuff while building the container * use prebuilt image for development * install pylint on base image * rename and use new kivy * tests: added tests for Array and CorrelationTest Both are not working due to errors * fix: Array no longer has *args and CorrelationTest functions no longer have self in the arguments * use new thing * use 20.04 base * symlink pip3 to pip * use pip instead of pip3 * tra_analysis v 2.1.0-alpha.2 SVM v 1.0.1 added unvalidated SVM unit tests Signed-off-by: ltcptgeneral <learthurgo@gmail.com> * fixed version number Signed-off-by: ltcptgeneral <learthurgo@gmail.com> * tests: added tests for ClassificationMetric * partially fixed and commented out svm unit tests * fixed some SVM unit tests * added installing pytest to devcontainer.json * fix: small fixes to KNN Namely, removing self from parameters and passing correct arguments to KNeighborsClassifier constructor * fix, test: Added tests for KNN and NaiveBayes. Also made some small fixes in KNN, NaiveBayes, and RegressionMetric * test: finished unit tests except for StatisticalTest Also made various small fixes and style changes * StatisticalTest v 1.0.1 * fixed RegressionMetric unit test temporarily disabled CorrelationTest unit tests * tra_analysis v 2.1.0-alpha.3 * readded __all__ * fix: floating point issues in unit tests for CorrelationTest Co-authored-by: AGawde05 <agawde05@gmail.com> Co-authored-by: ltcptgeneral <learthurgo@gmail.com> Co-authored-by: Dev Singh <dev@devksingh.com> Co-authored-by: jzpan1 <panzhenyu2014@gmail.com>
42 lines
1000 B
Python
42 lines
1000 B
Python
# Titan Robotics Team 2022: RegressionMetric submodule
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# Written by Arthur Lu
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# Notes:
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# this should be imported as a python module using 'from tra_analysis import RegressionMetric'
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# setup:
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__version__ = "1.0.0"
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__changelog__ = """changelog:
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1.0.0:
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- ported analysis.RegressionMetric() here
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"""
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__author__ = (
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"Arthur Lu <learthurgo@gmail.com>",
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)
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__all__ = [
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'RegressionMetric'
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]
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import numpy as np
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import sklearn
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from sklearn import metrics
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class RegressionMetric():
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def __new__(cls, predictions, targets):
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return cls.r_squared(cls, predictions, targets), cls.mse(cls, predictions, targets), cls.rms(cls, predictions, targets)
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def r_squared(self, predictions, targets): # assumes equal size inputs
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return sklearn.metrics.r2_score(targets, predictions)
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def mse(self, predictions, targets):
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return sklearn.metrics.mean_squared_error(targets, predictions)
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def rms(self, predictions, targets):
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return np.sqrt(sklearn.metrics.mean_squared_error(targets, predictions)) |