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analysis.py v 1.1.6.002
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# current benchmark of optimization: 1.33 times faster
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# current benchmark of optimization: 1.33 times faster
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# setup:
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# setup:
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__version__ = "1.1.6.001"
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__version__ = "1.1.6.002"
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# changelog should be viewed using print(analysis.__changelog__)
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# changelog should be viewed using print(analysis.__changelog__)
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__changelog__ = """changelog:
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__changelog__ = """changelog:
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1.1.6.001:
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1.1.6.002:
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- added additional hyperparameters to decisiontree()
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- changed layout of __changelog to be vscode friendly
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1.1.6.000:
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1.1.6.001:
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- fixed __version__
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- added additional hyperparameters to decisiontree()
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- fixed __all__ order
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1.1.6.000:
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- added decisiontree()
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- fixed __version__
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1.1.5.003:
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- fixed __all__ order
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- added pca
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- added decisiontree()
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1.1.5.002:
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1.1.5.003:
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- reduced import list
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- added pca
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- added kmeans clustering engine
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1.1.5.002:
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1.1.5.001:
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- reduced import list
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- simplified regression by using .to(device)
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- added kmeans clustering engine
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1.1.5.000:
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1.1.5.001:
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- added polynomial regression to regression(); untested
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- simplified regression by using .to(device)
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1.1.4.000:
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1.1.5.000:
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- added trueskill()
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- added polynomial regression to regression(); untested
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1.1.3.002:
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1.1.4.000:
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- renamed regression class to Regression, regression_engine() to regression gliko2_engine class to Gliko2
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- added trueskill()
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1.1.3.001:
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1.1.3.002:
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- changed glicko2() to return tuple instead of array
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- renamed regression class to Regression, regression_engine() to regression gliko2_engine class to Gliko2
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1.1.3.000:
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1.1.3.001:
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- added glicko2_engine class and glicko()
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- changed glicko2() to return tuple instead of array
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- verified glicko2() accuracy
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1.1.3.000:
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1.1.2.003:
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- added glicko2_engine class and glicko()
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- fixed elo()
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- verified glicko2() accuracy
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1.1.2.002:
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1.1.2.003:
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- added elo()
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- fixed elo()
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- elo() has bugs to be fixed
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1.1.2.002:
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1.1.2.001:
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- added elo()
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- readded regrression import
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- elo() has bugs to be fixed
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1.1.2.000:
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1.1.2.001:
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- integrated regression.py as regression class
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- readded regrression import
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- removed regression import
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1.1.2.000:
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- fixed metadata for regression class
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- integrated regression.py as regression class
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- fixed metadata for analysis class
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- removed regression import
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1.1.1.001:
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- fixed metadata for regression class
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- regression_engine() bug fixes, now actaully regresses
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- fixed metadata for analysis class
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1.1.1.000:
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1.1.1.001:
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- added regression_engine()
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- regression_engine() bug fixes, now actaully regresses
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- added all regressions except polynomial
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1.1.1.000:
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1.1.0.007:
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- added regression_engine()
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- updated _init_device()
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- added all regressions except polynomial
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1.1.0.006:
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1.1.0.007:
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- removed useless try statements
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- updated _init_device()
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1.1.0.005:
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1.1.0.006:
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- removed impossible outcomes
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- removed useless try statements
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1.1.0.004:
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1.1.0.005:
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- added performance metrics (r^2, mse, rms)
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- removed impossible outcomes
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1.1.0.003:
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1.1.0.004:
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- resolved nopython mode for mean, median, stdev, variance
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- added performance metrics (r^2, mse, rms)
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1.1.0.002:
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1.1.0.003:
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- snapped (removed) majority of uneeded imports
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- resolved nopython mode for mean, median, stdev, variance
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- forced object mode (bad) on all jit
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1.1.0.002:
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- TODO: stop numba complaining about not being able to compile in nopython mode
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- snapped (removed) majority of uneeded imports
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1.1.0.001:
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- forced object mode (bad) on all jit
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- removed from sklearn import * to resolve uneeded wildcard imports
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- TODO: stop numba complaining about not being able to compile in nopython mode
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1.1.0.000:
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1.1.0.001:
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- removed c_entities,nc_entities,obstacles,objectives from __all__
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- removed from sklearn import * to resolve uneeded wildcard imports
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- applied numba.jit to all functions
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1.1.0.000:
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- depreciated and removed stdev_z_split
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- removed c_entities,nc_entities,obstacles,objectives from __all__
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- cleaned up histo_analysis to include numpy and numba.jit optimizations
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- applied numba.jit to all functions
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- depreciated and removed all regression functions in favor of future pytorch optimizer
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- depreciated and removed stdev_z_split
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- depreciated and removed all nonessential functions (basic_analysis, benchmark, strip_data)
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- cleaned up histo_analysis to include numpy and numba.jit optimizations
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- optimized z_normalize using sklearn.preprocessing.normalize
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- depreciated and removed all regression functions in favor of future pytorch optimizer
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- TODO: implement kernel/function based pytorch regression optimizer
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- depreciated and removed all nonessential functions (basic_analysis, benchmark, strip_data)
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1.0.9.000:
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- optimized z_normalize using sklearn.preprocessing.normalize
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- refactored
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- TODO: implement kernel/function based pytorch regression optimizer
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- numpyed everything
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1.0.9.000:
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- removed stats in favor of numpy functions
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- refactored
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1.0.8.005:
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- numpyed everything
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- minor fixes
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- removed stats in favor of numpy functions
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1.0.8.004:
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1.0.8.005:
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- removed a few unused dependencies
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- minor fixes
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1.0.8.003:
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1.0.8.004:
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- added p_value function
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- removed a few unused dependencies
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1.0.8.002:
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1.0.8.003:
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- updated __all__ correctly to contain changes made in v 1.0.8.000 and v 1.0.8.001
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- added p_value function
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1.0.8.001:
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1.0.8.002:
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- refactors
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- updated __all__ correctly to contain changes made in v 1.0.8.000 and v 1.0.8.001
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- bugfixes
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1.0.8.001:
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1.0.8.000:
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- refactors
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- depreciated histo_analysis_old
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- bugfixes
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- depreciated debug
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1.0.8.000:
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- altered basic_analysis to take array data instead of filepath
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- depreciated histo_analysis_old
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- refactor
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- depreciated debug
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- optimization
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- altered basic_analysis to take array data instead of filepath
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1.0.7.002:
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- refactor
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- bug fixes
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- optimization
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1.0.7.001:
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1.0.7.002:
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- bug fixes
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- bug fixes
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1.0.7.000:
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1.0.7.001:
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- added tanh_regression (logistical regression)
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- bug fixes
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- bug fixes
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1.0.7.000:
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1.0.6.005:
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- added tanh_regression (logistical regression)
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- added z_normalize function to normalize dataset
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- bug fixes
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- bug fixes
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1.0.6.005:
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1.0.6.004:
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- added z_normalize function to normalize dataset
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- bug fixes
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- bug fixes
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1.0.6.003:
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1.0.6.004:
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- bug fixes
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- bug fixes
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1.0.6.002:
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1.0.6.003:
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- bug fixes
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- bug fixes
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1.0.6.001:
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1.0.6.002:
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- corrected __all__ to contain all of the functions
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- bug fixes
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1.0.6.000:
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1.0.6.001:
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- added calc_overfit, which calculates two measures of overfit, error and performance
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- corrected __all__ to contain all of the functions
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- added calculating overfit to optimize_regression
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1.0.6.000:
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1.0.5.000:
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- added calc_overfit, which calculates two measures of overfit, error and performance
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- added optimize_regression function, which is a sample function to find the optimal regressions
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- added calculating overfit to optimize_regression
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- optimize_regression function filters out some overfit funtions (functions with r^2 = 1)
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1.0.5.000:
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- planned addition: overfit detection in the optimize_regression function
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- added optimize_regression function, which is a sample function to find the optimal regressions
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1.0.4.002:
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- optimize_regression function filters out some overfit funtions (functions with r^2 = 1)
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- added __changelog__
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- planned addition: overfit detection in the optimize_regression function
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- updated debug function with log and exponential regressions
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1.0.4.002:
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1.0.4.001:
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- added __changelog__
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- added log regressions
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- updated debug function with log and exponential regressions
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- added exponential regressions
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1.0.4.001:
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- added log_regression and exp_regression to __all__
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- added log regressions
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1.0.3.008:
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- added exponential regressions
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- added debug function to further consolidate functions
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- added log_regression and exp_regression to __all__
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1.0.3.007:
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1.0.3.008:
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- added builtin benchmark function
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- added debug function to further consolidate functions
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- added builtin random (linear) data generation function
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1.0.3.007:
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- added device initialization (_init_device)
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- added builtin benchmark function
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1.0.3.006:
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- added builtin random (linear) data generation function
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- reorganized the imports list to be in alphabetical order
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- added device initialization (_init_device)
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- added search and regurgitate functions to c_entities, nc_entities, obstacles, objectives
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1.0.3.006:
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1.0.3.005:
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- reorganized the imports list to be in alphabetical order
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- major bug fixes
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- added search and regurgitate functions to c_entities, nc_entities, obstacles, objectives
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- updated historical analysis
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1.0.3.005:
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- depreciated old historical analysis
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- major bug fixes
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1.0.3.004:
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- updated historical analysis
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- added __version__, __author__, __all__
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- depreciated old historical analysis
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- added polynomial regression
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1.0.3.004:
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- added root mean squared function
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- added __version__, __author__, __all__
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- added r squared function
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- added polynomial regression
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1.0.3.003:
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- added root mean squared function
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- bug fixes
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- added r squared function
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- added c_entities
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1.0.3.003:
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1.0.3.002:
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- bug fixes
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- bug fixes
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- added c_entities
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- added nc_entities, obstacles, objectives
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1.0.3.002:
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- consolidated statistics.py to analysis.py
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- bug fixes
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1.0.3.001:
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- added nc_entities, obstacles, objectives
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- compiled 1d, column, and row basic stats into basic stats function
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- consolidated statistics.py to analysis.py
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1.0.3.000:
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1.0.3.001:
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- added historical analysis function
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- compiled 1d, column, and row basic stats into basic stats function
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1.0.2.xxx:
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1.0.3.000:
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- added z score test
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- added historical analysis function
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1.0.1.xxx:
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1.0.2.xxx:
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- major bug fixes
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- added z score test
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1.0.0.xxx:
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1.0.1.xxx:
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- added loading csv
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- major bug fixes
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- added 1d, column, row basic stats
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1.0.0.xxx:
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- added loading csv
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- added 1d, column, row basic stats
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"""
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"""
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__author__ = (
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__author__ = (
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