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Add algorithm options of KNeighborRegressor/Classifier; Add SelectFdr to selectors #1350

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Add algorithm options of KNeighborRegressor/Classifier; Add SelectFdr to selectors #1350

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10 changes: 9 additions & 1 deletion tpot/config/classifier.py
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Original file line number Diff line number Diff line change
Expand Up @@ -81,7 +81,8 @@
'sklearn.neighbors.KNeighborsClassifier': {
'n_neighbors': range(1, 101),
'weights': ["uniform", "distance"],
'p': [1, 2]
'p': [1, 2],
'algorithm': ["kd_tree", "ball_tree"] # using "brute" results in memory spikes
},

'sklearn.svm.LinearSVC': {
Expand Down Expand Up @@ -192,6 +193,13 @@
}
},

'sklearn.feature_selection.SelectFdr': {
'alpha': np.arange(0, 0.05, 0.001),
'score_func': {
'sklearn.feature_selection.f_classif': None
}
},

'sklearn.feature_selection.SelectPercentile': {
'percentile': range(1, 100),
'score_func': {
Expand Down
10 changes: 9 additions & 1 deletion tpot/config/regressor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -69,7 +69,8 @@
'sklearn.neighbors.KNeighborsRegressor': {
'n_neighbors': range(1, 101),
'weights': ["uniform", "distance"],
'p': [1, 2]
'p': [1, 2],
'algorithm': ["kd_tree", "ball_tree"] # using "brute" results in memory spikes
},

'sklearn.linear_model.LassoLarsCV': {
Expand Down Expand Up @@ -186,6 +187,13 @@
}
},

'sklearn.feature_selection.SelectFdr': {
'alpha': np.arange(0, 0.05, 0.001),
'score_func': {
'sklearn.feature_selection.f_regression': None
}
},

'sklearn.feature_selection.SelectPercentile': {
'percentile': range(1, 100),
'score_func': {
Expand Down