Skip to content

added Regressor Classifier #1191 #1193

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 1 commit into from
Closed

added Regressor Classifier #1191 #1193

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
22 changes: 21 additions & 1 deletion tpot/config/classifier.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@
"""

import numpy as np

from sklearn.gaussian_process.kernels import WhiteKernel, Matern, RBF, DotProduct, RationalQuadratic, ExpSineSquared, ConstantKernel
# Check the TPOT documentation for information on the structure of config dicts

classifier_config_dict = {
Expand Down Expand Up @@ -124,6 +124,26 @@
'learning_rate_init': [1e-3, 1e-2, 1e-1, 0.5, 1.]
},

'sklearn.gaussian_process.GaussianProcessClassifier': {
'kernel' : [1.0*RBF(length_scale=0.5, length_scale_bounds=(1e-05, 100000.0)),
1.0*RationalQuadratic(length_scale=0.5, alpha=0.1),
1.0*ExpSineSquared(length_scale=0.5, periodicity=3.0,
length_scale_bounds=(1e-05, 100000.0),
periodicity_bounds=(1.0, 10.0)),
ConstantKernel(0.1, (0.01, 10.0))*(DotProduct(sigma_0=1.0, sigma_0_bounds=(0.1, 10.0)) ** 2),
1.0**2*Matern(length_scale=0.5, length_scale_bounds=(1e-05, 100000.0),
nu=0.5)],
'alpha': [5e-9,1e-3, 1e-2, 1e-1, 1., 10., 100.],
'normalize_y' : [True, False],
'optimizer' : ['fmin_l_bfgs_b']
},

'sklearn.ensemble.AdaBoostClassifier': {
'n_estimators': [100],
'learning_rate': [1e-3, 1e-2, 1e-1, 0.5, 1.],
'loss': ["linear", "square", "exponential"]
},

# Preprocesssors
'sklearn.preprocessing.Binarizer': {
'threshold': np.arange(0.0, 1.01, 0.05)
Expand Down
21 changes: 20 additions & 1 deletion tpot/config/regressor.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@
"""

import numpy as np

from sklearn.gaussian_process.kernels import WhiteKernel, Matern, RBF, DotProduct, RationalQuadratic, ExpSineSquared, ConstantKernel
# Check the TPOT documentation for information on the structure of config dicts

regressor_config_dict = {
Expand Down Expand Up @@ -117,6 +117,25 @@
'power_t': [0.5, 0.0, 1.0, 0.1, 100.0, 10.0, 50.0]
},

'sklearn.gaussian_process.GaussianProcessRegressor': {
'kernel' : [1.0*RBF(length_scale=0.5, length_scale_bounds=(1e-05, 100000.0)),
1.0*RationalQuadratic(length_scale=0.5, alpha=0.1),
1.0*ExpSineSquared(length_scale=0.5, periodicity=3.0,
length_scale_bounds=(1e-05, 100000.0),
periodicity_bounds=(1.0, 10.0)),
ConstantKernel(0.1, (0.01, 10.0))*(DotProduct(sigma_0=1.0, sigma_0_bounds=(0.1, 10.0)) ** 2),
1.0**2*Matern(length_scale=0.5, length_scale_bounds=(1e-05, 100000.0),
nu=0.5)],
'alpha': [5e-9,1e-3, 1e-2, 1e-1, 1., 10., 100.],
'normalize_y' : [True, False],
'optimizer' : ['fmin_l_bfgs_b']
},

'sklearn.ensemble.AdaBoostClassifier': {
'n_estimators': [100],
'learning_rate': [1e-3, 1e-2, 1e-1, 0.5, 1.],
'loss': ["linear", "square", "exponential"]
},
# Preprocessors
'sklearn.preprocessing.Binarizer': {
'threshold': np.arange(0.0, 1.01, 0.05)
Expand Down