updated pycaret-nightly==0.18 (part 1)

pycaret/classification.py

@@ -3983,14 +3983,14 @@ def compare_models(blacklist = None,
 
     Parameters
     ----------
-    blacklist: string, default = None
+    blacklist: list of strings, default = None
     In order to omit certain models from the comparison, the abbreviation string 
-    (see above list) can be passed as list in blacklist param. This is normally
-    done to be more efficient with time.
+    (see above list) can be passed as list of string in blacklist param. This is 
+    normally done to be more efficient with time.
 
-    whitelist: string, default = None
+    whitelist: list of strings, default = None
     In order to run only certain models for the comparison, the abbreviation string 
-    (see above list) can be passed as a list in whitelist param. 
+    (see above list) can be passed as a list of strings in whitelist param. 
 
     fold: integer, default = 10
     Number of folds to be used in Kfold CV. Must be at least 2. 

pycaret/regression.py

@@ -3292,14 +3292,14 @@ def compare_models(blacklist = None,
         
     Parameters
     ----------
-    blacklist: string, default = None
+    blacklist: list of strings, default = None
     In order to omit certain models from the comparison, the abbreviation string 
-    (see above list) can be passed as list in blacklist param. This is normally
-    done to be more efficient with time. 
+    (see above list) can be passed as list of strings in blacklist param. This is 
+    normally done to be more efficient with time. 
 
-    whitelist: string, default = None
+    whitelist: list of strings, default = None
     In order to run only certain models for the comparison, the abbreviation string 
-    (see above list) can be passed as a list in whitelist param. 
+    (see above list) can be passed as a list of strings in whitelist param. 
 
     fold: integer, default = 10
     Number of folds to be used in Kfold CV. Must be at least 2. 
@@ -7902,11 +7902,11 @@ def plot_model(estimator,
         clear_output()
         if save:
             if system:
-                visualizer.show(outpath="Validation Curve.png")
+                viz.show(outpath="Validation Curve.png")
             else:
-                visualizer.show(outpath="Validation Curve.png", clear_figure=True)
+                viz.show(outpath="Validation Curve.png", clear_figure=True)
         else:
-            visualizer.show()
+            viz.show()
         
     elif plot == 'feature':
         if hasattr(estimator, 'coef_'):

pycaret/utils.py

@@ -3,7 +3,7 @@
 # License: MIT
 
 def version():
-    print("pycaret-nightly-0.17")
+    print("pycaret-nightly-0.18")
 
 
 def check_metric(actual, prediction, metric, round=4):

setup.py

@@ -13,7 +13,7 @@ with open('requirements.txt') as f:
 
 setup(
     name="pycaret-nightly",
-    version="0.17",
+    version="0.18",
     description="Nightly build of PyCaret - An open source, low-code machine learning library in Python.",
     long_description=readme(),
     long_description_content_type="text/markdown",