Add nodes, leaves, depth to mysql

Add nodes, leaves, depth, samples, features and classes to analysis

experimentation/Experiments.py

@@ -2,9 +2,8 @@ import json
 import os
 import time
 import warnings
-
+import numpy as np
 from sklearn.model_selection import GridSearchCV, cross_validate
-
 from . import Models
 from .Database import Hyperparameters, MySQL, Outcomes
 from .Sets import Datasets
@@ -94,15 +93,25 @@ class Experiment:
                     X,
                     y,
                     return_train_score=True,
+                    return_estimator=True,
                     n_jobs=self._threads,
                     cv=kfold,
                 )
                 for item in outcomes:
                     total[item].append(results[item])
         print("end")
+        if type(model).__name__ == "Stree":
+            best_model = results["estimator"][np.argmax(results["test_score"])]
+            nodes, leaves = best_model.nodes_leaves()
+            depth = best_model.depth_
+        else:
+            nodes = leaves = depth = 0
+        complexity = dict(nodes=nodes, leaves=leaves, depth=depth)
         outcomes = Outcomes(host=self._host, model=self._model_name)
         parameters = json.dumps(parameters, sort_keys=True)
-        outcomes.store(dataset, normalize, standardize, parameters, total)
+        outcomes.store(
+            dataset, normalize, standardize, parameters, total, complexity
+        )
         if self._num_warnings > 0:
             print(f"{self._num_warnings} warnings have happend")