diff --git a/main_run_ml_.py b/main_run_ml_.py
new file mode 100644
index 0000000000000000000000000000000000000000..f143fba8744ba9158bb2712963206afabf66a599
--- /dev/null
+++ b/main_run_ml_.py
@@ -0,0 +1,37 @@
+import os
+import warnings
+warnings.filterwarnings("ignore")
+
+
+from kit.mics import *
+from kit.Machine_learning import *
+
+data_path = 'data/'
+results_path = 'results/'
+
+
+params = 'default'
+merge_list = 'no'
+names_classifiers = 'default'
+selected_material = 'all'
+
+selected_df = read_material_csv(data_path,merge_list,selected_material)
+
+#write setting to txt file
+save_folder = 'results/'
+if not os.path.exists(os.path.join(results_path,save_folder)):
+    os.makedirs(os.path.join(results_path,save_folder))
+    print('Make new folder due to directory not exist')
+
+with open(os.path.join(results_path,save_folder,'setting.txt'),'w') as f:
+    for data,name in zip([names_classifiers,selected_material,merge_list,params],['names_classifiers','selected_material','merge_list','params']):
+        f.write(name)
+        f.write('\n')
+        f.writelines(str(data))
+        f.write('\n,\n')
+        print(name,'\n',data,'\n','*'*30)
+    f.write(results_path)
+
+train_mymodel(selected_df, results_path,
+    names_classifiers=names_classifiers,
+    epochs=50,params=params,extra_cmt='default',fixseed=True)