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thieu1995 · Jan 2, 2024 · c4b5dbe · c4b5dbe
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Showing 4 changed files with 8 additions and 8 deletions.
diff --git a/docs/source/pages/general/advances/log_training_process.rst b/docs/source/pages/general/advances/log_training_process.rst
@@ -9,14 +9,14 @@ the log process.
 .. code-block:: python
 
    problem_dict1 = {
-      "fit_func": F5,
+      "obj_func": F5,
       "bounds": FloatVar(lb=[-3, -5, 1, -10, ], ub=[5, 10, 100, 30, ]),
       "minmax": "min",
       # Default = "console"
    }
 
    problem_dict1 = {
-      "fit_func": F5,
+      "obj_func": F5,
       "bounds": FloatVar(lb=[-3, -5, 1, -10, ], ub=[5, 10, 100, 30, ]),
       "minmax": "min",
       "log_to": "console",
@@ -28,7 +28,7 @@ the log process.
 .. code-block:: python
 
    problem_dict2 = {
-      "fit_func": F5,
+      "obj_func": F5,
       "bounds": FloatVar(lb=[-3, -5, 1, -10, ], ub=[5, 10, 100, 30, ]),
       "minmax": "min",
       "log_to": "file",
@@ -41,7 +41,7 @@ the log process.
 .. code-block:: python
 
    problem_dict3 = {
-      "fit_func": F5,
+      "obj_func": F5,
       "bounds": FloatVar(lb=[-3, -5, 1, -10, ], ub=[5, 10, 100, 30, ]),
       "minmax": "min",
       "log_to": None,

diff --git a/docs/source/pages/general/advances/model_parameter.rst b/docs/source/pages/general/advances/model_parameter.rst
@@ -28,7 +28,7 @@ can help you determine how to set valid parameters.
    from mealpy import DE, FloatVar
 
    problem = {
-      "fit_func": F5,
+      "obj_func": F5,
       "bounds": FloatVar(lb=[-10,]*10, ub=[30,]*10),
       "minmax": "min",
    }
@@ -54,7 +54,7 @@ This will definitely be helpful when using ParameterGrid/GridSearchCV from the s
 	from mealpy import DE, FloatVar
 
 	problem = {
-		"fit_func": F5,
+		"obj_func": F5,
 		"bounds": FloatVar(lb=[-10,]*10, ub=[30,]*10),
 		"minmax": "min",
 	}

diff --git a/docs/source/pages/general/advances/model_problem_name.rst b/docs/source/pages/general/advances/model_problem_name.rst
@@ -12,7 +12,7 @@ problem, especially in multitask problems.
    from mealpy.swarm_based import PSO
 
    problem = {
-      "fit_func": F5,
+      "obj_func": F5,
       "bounds": FloatVar(lb=[-3, -5, 1, -10, ], ub=[5, 10, 100, 30, ]),
       "minmax": "min",
       "name": "Benchmark Function 5th"

diff --git a/docs/source/pages/general/advances/starting_positions.rst b/docs/source/pages/general/advances/starting_positions.rst
@@ -20,7 +20,7 @@ Not recommended to use this utility. But in case you need this:
 		return result
 
 	fm_problem = {
-		"fit_func": frequency_modulated,
+		"obj_func": frequency_modulated,
 		"bounds": FloatVar(lb=[-6.4, ] * 6, ub=[6.35, ] * 6),
 		"minmax": "min",
 		"log_to": "console",