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feat(Sweep): try to filter out some not great models (#144)

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* feat(Sweep): try to filter out some not great models

* fix(Sweep): yaml

* fix(Sweep): yaml

* fix(Config): remove some models that do not perform well
This commit is contained in:
Mark Aron Szulyovszky
2022-01-11 10:33:18 +01:00
committed by GitHub
parent 2c03959315
commit 54ea59c0cf
3 changed files with 12 additions and 8 deletions
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models/model_map.py
+1 -2
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@@ -5,7 +5,7 @@ from sklearn.tree import DecisionTreeClassifier
from sklearnex.neighbors import KNeighborsRegressor, KNeighborsClassifier
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearnex.svm import SVR, SVC
from sklearn.naive_bayes import GaussianNB, MultinomialNB
from sklearn.naive_bayes import GaussianNB
from sklearn.neural_network import MLPRegressor, MLPClassifier
from sklearn.ensemble import AdaBoostRegressor, RandomForestRegressor, ExtraTreesRegressor, AdaBoostClassifier, GradientBoostingClassifier, ExtraTreesClassifier
from sklearnex.ensemble import RandomForestClassifier
@@ -51,7 +51,6 @@ model_map = {
KNN= SKLearnModel(KNeighborsClassifier()),
CART= SKLearnModel(DecisionTreeClassifier(max_depth=15, random_state=1)),
NB= SKLearnModel(GaussianNB()),
MNB = SKLearnModel(MultinomialNB()),
AB= SKLearnModel(AdaBoostClassifier(n_estimators=15)),
RF= SKLearnModel(RandomForestClassifier(n_jobs=-1, max_depth=20, random_state=1)),
SVC = SKLearnModel(SVC(kernel='rbf', C=1e3, probability=True, random_state=1)),