|
@@ -21,10 +21,8 @@ def my_accuracy_scorer(*args):
|
|
|
|
|
|
def _get_best_model(X_train, y_train):
|
|
def _get_best_model(X_train, y_train):
|
|
|
|
|
|
- #Cs = [0.001, 0.01, 0.1, 1, 10, 100, 1000]
|
|
|
|
- Cs = [1, 2, 4, 8, 16, 32]
|
|
|
|
- # gammas = [0.001, 0.01, 0.1, 1, 5, 10, 100]
|
|
|
|
- gammas = [0.001, 0.1, 1, 10, 100]
|
|
|
|
|
|
+ Cs = [0.001, 0.01, 0.1, 1, 2, 5, 10, 100, 1000]
|
|
|
|
+ gammas = [0.001, 0.01, 0.1, 1, 2, 5, 10, 100]
|
|
param_grid = {'kernel':['rbf'], 'C': Cs, 'gamma' : gammas}
|
|
param_grid = {'kernel':['rbf'], 'C': Cs, 'gamma' : gammas}
|
|
|
|
|
|
svc = svm.SVC(probability=True, class_weight='balanced')
|
|
svc = svm.SVC(probability=True, class_weight='balanced')
|