New initial assumption

fedot/api/api_utils/assumptions/task_assumptions.py

@@ -91,6 +91,15 @@ class RegressionAssumptions(TaskAssumptions):
     @property
     def builders(self):
         return {
+            'gbm_linear': PipelineBuilder().
+            add_branch('catboostreg', 'xgboostreg', 'lgbmreg').join_branches('ridge'),
+            'xgb_lgbm_linear': PipelineBuilder().
+            add_branch('xgboostreg', 'lgbmreg').join_branches('ridge'),
+            'gbm_rf_linear': PipelineBuilder().
+            add_branch('catboostreg', 'xgboostreg', 'lgbmreg', 'rfr').join_branches('ridge'),
+            'catboostreg': PipelineBuilder().add_node('catboostreg'),
+            'xgboostreg': PipelineBuilder().add_node('xgboostreg'),
+            'lgbmreg': PipelineBuilder().add_node('lgbmreg'),
             'rfr': PipelineBuilder().add_node('rfr'),
             'ridge': PipelineBuilder().add_node('ridge'),
         }
@@ -112,9 +121,17 @@ class ClassificationAssumptions(TaskAssumptions):
     @property
     def builders(self):
         return {
+            'gbm_linear': PipelineBuilder().
+            add_branch('catboost', 'xgboost', 'lgbm').join_branches('logit'),
+            'xgb_lgbm_linear': PipelineBuilder().
+            add_branch('xgboost', 'lgbm').join_branches('logit'),
+            'gbm_rf_linear': PipelineBuilder().
+            add_branch('catboost', 'xgboost', 'lgbm', 'rf').join_branches('logit'),
+            'catboost': PipelineBuilder().add_node('catboost'),
+            'xgboost': PipelineBuilder().add_node('xgboost'),
+            'lgbm': PipelineBuilder().add_node('lgbm'),
             'rf': PipelineBuilder().add_node('rf'),
             'logit': PipelineBuilder().add_node('logit'),
-            'catboost': PipelineBuilder().add_node('catboost'),
         }
 
     def ensemble_operation(self) -> str:

fedot/core/repository/data/default_operation_params.json

@@ -24,24 +24,50 @@
     "early_stopping_rounds": 30
   },
   "catboost": {
-    "allow_writing_files": false,
+    "n_jobs": -1,
+    "num_trees": 3000,
+    "learning_rate": 0.03,
+    "l2_leaf_reg": 1e-2,
+    "bootstrap_type": "Bernoulli",
+    "grow_policy": "SymmetricTree",
+    "max_depth": 5,
+    "min_data_in_leaf": 1,
+    "one_hot_max_size": 10,
+    "fold_permutation_block": 1,
+    "boosting_type": "Plain",
+    "od_type": "Iter",
+    "od_wait": 100,
+    "max_bin": 32,
+    "feature_border_type": "GreedyLogSum",
+    "nan_mode": "Min",
     "verbose": false,
-    "iterations": 1000,
-    "enable_categorical": true,
+    "allow_writing_files": false,
     "use_eval_set": true,
     "use_best_model": true,
-    "early_stopping_rounds": 30,
-    "n_jobs": 1
+    "enable_categorical": true
   },
   "catboostreg": {
-    "allow_writing_files": false,
+    "n_jobs": -1,
+    "num_trees": 3000,
+    "learning_rate": 0.03,
+    "l2_leaf_reg": 1e-2,
+    "bootstrap_type": "Bernoulli",
+    "grow_policy": "SymmetricTree",
+    "max_depth": 5,
+    "min_data_in_leaf": 1,
+    "one_hot_max_size": 10,
+    "fold_permutation_block": 1,
+    "boosting_type": "Plain",
+    "od_type": "Iter",
+    "od_wait": 100,
+    "max_bin": 32,
+    "feature_border_type": "GreedyLogSum",
+    "nan_mode": "Min",
     "verbose": false,
-    "iterations": 1000,
-    "enable_categorical": true,
+    "allow_writing_files": false,
     "use_eval_set": true,
     "use_best_model": true,
-    "early_stopping_rounds": 30,
-    "n_jobs": 1
+    "enable_categorical": true
   },
   "lgbm": {
     "boosting_type": "gbdt",