update number of evaluated solutions for learning process

find_best_attributes_surrogate_openML_multi_specific.py

@@ -243,7 +243,7 @@ def main():
     policy = RandomPolicy(operators)
 
     # custom start surrogate variable based on problem size
-    p_start = int(0.2 * problem_size)
+    p_start = int(problem_size / p_k_division * 3) # 3 \times number of features for each sub-model
 
     # fixed minimal number of real evaluations
     if p_start < 50: