diff options
| -rw-r--r-- | tree.py | 7 |
1 files changed, 4 insertions, 3 deletions
@@ -202,7 +202,7 @@ def bestsplit(x, y, min_leaf) -> None: # twee "x rows" arrays we moeten returnen, en welke split value het beste # was natuurlijk. - # Hieren stoppen we (rows for children, delta_i, split value, col will be added later) + # Hieren stacken we arrays onder (rows for children, delta_i, split value, col will be added later) best_array = np.zeros((split_points.shape[0], x.shape[0] + 3), dtype='float64') # print(f"{best_array=}") # Stop wanneer de array met split points leeg is @@ -255,7 +255,7 @@ def exhaustive_split_search(rows, classes, min_leaf): print("\t\t->entering exhaustive split search") # We hebben enumerate nodig, want we willen weten op welke col # (age,married,house,income,gender) we een split doen - exhaustive_best_array = np.zeros((1, rows.shape[0] + 3), dtype='float64') + exhaustive_best_array = [] print(f"Rows:\n{rows},\n Classes:\n{classes}") for i, col in enumerate(rows.transpose()): # calculate the best split for the col that satisfies the min_leaf @@ -263,7 +263,8 @@ def exhaustive_split_search(rows, classes, min_leaf): best_array_for_col = bestsplit(col, classes, min_leaf) # add col number to rows best_array_for_col[:,-1] = i - exhaustive_best_array = np.vstack((exhaustive_best_array, best_array_for_col)) + exhaustive_best_array.append(best_array_for_col) + exhaustive_best_array = np.concatenate(exhaustive_best_array) print("The array with exhaustive splits is\n", exhaustive_best_array) print("\t\t->returning from exhaustive split search") return exhaustive_best_array |