add cross val. and lazy cross val. Pt.4

examples/cross_val.py

@@ -7,7 +7,7 @@
 from sklearn.metrics import accuracy_score
 from time import time
 
-print(f"\n ----- Running: {os.path.basename(__file__)}... ----- \n")
+print(f"\n ----- Running: {os.path.basename(__file__)}... ----- \n")    
 
 dataset = load_breast_cancer()
 X, y = dataset.data, dataset.target

examples/lazy_cross_val.py

@@ -9,13 +9,34 @@
 
 print(f"\n ----- Running: {os.path.basename(__file__)}... ----- \n")
 
-dataset = load_iris()
+dataset = load_breast_cancer()
 X, y = dataset.data, dataset.target
 X_train, X_test, y_train, y_test = train_test_split(
     X, y, test_size=0.2, random_state=42
 )
 
-res3 = ub.lazy_cross_val_optim(
+# start = time()
+# res3 = ub.lazy_cross_val_optim(
+#     X_train,
+#     y_train,
+#     X_test=X_test,
+#     y_test=y_test,
+#     model_type="lightgbm",
+#     type_fit="classification",
+#     scoring="accuracy",
+#     n_estimators=100,
+#     cv=5,
+#     n_jobs=None,
+#     n_init=10,
+#     n_iter=190,
+#     abs_tol=1e-3,
+#     seed=123,
+#     customize=True
+# )
+# print(f"Elapsed: {time()-start}")
+
+start = time()
+res4 = ub.lazy_cross_val_optim(
     X_train,
     y_train,
     X_test=X_test,
@@ -30,5 +51,8 @@
     n_iter=190,
     abs_tol=1e-3,
     seed=123,
+    customize=False
 )
-print(res3)
+print(f"Elapsed: {time()-start}")
+#print(res3)
+print(res4)

requirements.txt

@@ -4,4 +4,5 @@ scikit-learn
 xgboost
 lightgbm
 catboost
-GPopt
+GPopt
+nnetsauce 

setup.py

@@ -9,7 +9,7 @@
 
 subprocess.check_call(['pip', 'install', 'Cython'])
 
-__version__ = "0.4.1"
+__version__ = "0.4.2"
 
 here = path.abspath(path.dirname(__file__))
 

unifiedbooster/__init__.py

@@ -3,5 +3,10 @@
 from .gbdt_regression import GBDTRegressor
 from .gpoptimization import cross_val_optim, lazy_cross_val_optim
 
-__all__ = ["GBDT", "GBDTClassifier", "GBDTRegressor", 
-           "cross_val_optim", "lazy_cross_val_optim"]
+__all__ = [
+    "GBDT",
+    "GBDTClassifier",
+    "GBDTRegressor",
+    "cross_val_optim",
+    "lazy_cross_val_optim",
+]

unifiedbooster/gbdt_classification.py

@@ -1,17 +1,18 @@
 from .gbdt import GBDT
 from sklearn.base import ClassifierMixin
+
 try:
     from xgboost import XGBClassifier
-except: 
-    pass 
+except:
+    pass
 try:
     from catboost import CatBoostClassifier
 except:
     pass
-try: 
+try:
     from lightgbm import LGBMClassifier
 except:
-    pass 
+    pass
 from sklearn.ensemble import GradientBoostingClassifier
 
 

unifiedbooster/gbdt_regression.py

@@ -1,17 +1,18 @@
 from .gbdt import GBDT
 from sklearn.base import RegressorMixin
-try: 
+
+try:
     from xgboost import XGBRegressor
 except:
-    pass 
+    pass
 try:
     from catboost import CatBoostRegressor
 except:
-    pass 
-try: 
+    pass
+try:
     from lightgbm import LGBMRegressor
 except:
-    pass 
+    pass
 from sklearn.ensemble import GradientBoostingRegressor