diff --git a/.idea/misc.xml b/.idea/misc.xml
index 8eab719..715ed69 100644
--- a/.idea/misc.xml
+++ b/.idea/misc.xml
@@ -3,5 +3,5 @@
-
+
\ No newline at end of file
diff --git a/.idea/wozek.iml b/.idea/wozek.iml
index 004f809..b1bd648 100644
--- a/.idea/wozek.iml
+++ b/.idea/wozek.iml
@@ -4,7 +4,7 @@
-
+
\ No newline at end of file
diff --git a/__pycache__/data.cpython-37.pyc b/__pycache__/data.cpython-37.pyc
index 196eabc..6a5342b 100644
Binary files a/__pycache__/data.cpython-37.pyc and b/__pycache__/data.cpython-37.pyc differ
diff --git a/__pycache__/decision_tree.cpython-37.pyc b/__pycache__/decision_tree.cpython-37.pyc
index 5b41fdd..ae6781a 100644
Binary files a/__pycache__/decision_tree.cpython-37.pyc and b/__pycache__/decision_tree.cpython-37.pyc differ
diff --git a/data.py b/data.py
index b8e059f..4c3a444 100644
--- a/data.py
+++ b/data.py
@@ -40,7 +40,7 @@ learning_data = [
['gold', 'rectangle', 40, 'medium', 'Twix'],
['gold', 'rectangle', 50, 'medium', 'Prince-polo'],
['brown', 'rectangle', 55, 'medium', 'Snickers'],
- ['brown', 'rectangle', 45, 'medium', 'Lion'],
+ ['brown', 'rectangle', 45, 'medium', 'Lion'],
['white', 'rectangle', 40, 'medium', 'Kinder-bueno'],
['red', 'rectangle', 50, 'medium', 'Kit-kat'],
['blue', 'rectangle', 115, 'big', 'Wedel'],
diff --git a/decision_tree.py b/decision_tree.py
index 1f6c05b..48a1d3a 100644
--- a/decision_tree.py
+++ b/decision_tree.py
@@ -62,15 +62,14 @@ def partition(rows, question):
def gini(rows):
- """ Gini impurity is a measure of how often a randomly chosen element from
- the set would be incorrectly labeled if it was randomly labeled according to
- the distribution of labels in the subset. """
+ """ Gini impurity to miara tego jak często losowo wybrany element zbioru byłby źle skategoryzowany, gdyby
+ przypisać mu losową kategorię spośród wszystkich kategorii znajdujących się w danym zbiorze. """
counts = class_counts(rows)
- impurity = 1
+ impurity = 0
for lbl in counts:
prob_of_lbl = counts[lbl] / float(len(rows))
- impurity -= prob_of_lbl ** 2
+ impurity += prob_of_lbl * (1 - prob_of_lbl)
return impurity
@@ -169,16 +168,15 @@ def print_leaf(counts):
# print_tree(my_tree)
#
# testing_data = [
-# ['gold', 'rectangle', 50, 'medium', 'Name'],
-# ['brown', 'rectangle', 55, 'medium', 'Snickers'],
-# ['white', 'rectangle', 120, 'big', 'Name']
+# ['red', 'rectangle', 50, 'medium', 'Kit-kat'],
+# ['blue', 'rectangle', 115, 'big', 'Wedel'],
+# ['white', 'rectangle', 15, 'small', 'Krowka'],
# ]
#
-# test = ['white', 'rectangle', 120, 'big', 'Name']
+# test = ['white', 'rectangle', 15, 'small', 'Krowka']
#
-# # for row in testing_data:
-# # print(print_leaf(classify(row, my_tree)))
+# for row in testing_data:
+# print(print_leaf(classify(row, my_tree)))
#
# wynik = print_leaf(classify(test, my_tree))[0]
# print(wynik)
-
diff --git a/environment.yml b/environment.yml
index 2d225c4..2d49dc6 100644
Binary files a/environment.yml and b/environment.yml differ
diff --git a/img/shelf.png b/img/shelf.png
index 3e443f0..47b4aa4 100644
Binary files a/img/shelf.png and b/img/shelf.png differ
diff --git a/main.py b/main.py
index cb61a47..177f331 100644
--- a/main.py
+++ b/main.py
@@ -11,6 +11,7 @@ from board import create_board, draw_board
from random import randint, choice
from mcda import choseProducts
+
# Inicjalizacja programu i utworzenie obiektu ekrany
def run():
pygame.init()
@@ -44,7 +45,6 @@ def run():
agent.turn_left()
elif event.key == pygame.K_UP:
agent.move_forward(board)
- print(agent.x, agent.y)
elif event.key == pygame.K_SPACE:
board[9][0].item = choice(data.learning_data)
print("Wybrano: " + board[9][0].item[-1])