Оновити 'raport.md'
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raport.md
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raport.md
@ -9,32 +9,15 @@ Użyłem drzew decyzyjnych.
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Potrawy, ich nazwa, rodzaj oraz charakterystyka.
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Potrawy, ich nazwa, rodzaj oraz charakterystyka.
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tree_format = ["dish", "served", "price", "origin", "cooked", "ingredients", "name"]
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menu = Context.fromstring(''' |meat|salad|meal|drink|cold|hot |
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Pork | X | | | | | X |
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Espresso | | | | X | | X |
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Latte | | | | X | | X |
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Green Tea | | | | X | X | |
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Greek Salad| | X | | | X | |
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Pizza | | | X | | | X |''')
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Dane uczące:
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Dane uczące:
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training_data = [
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dish - (salad/soup/meal/coffee/tea/non-alcho drink)
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['meat','hot','Pork'],
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served - (cold/hot/warm)
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['salad','cold','Greek Salad'],
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origin - (Worldwide/America/Europe/Asia)
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['drink','hot','Espresso'],
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cooked - (baked/boiled/mixed)
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['drink','hot','Latte'],
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ingridients - (2/4)
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['drink','cold','Green Tea'],
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['meal','hot','Pizza'],
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['meal','cold','Wheat Pita'],
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]
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Dane testowe jest tworzone losowo w funkcji:
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Dane testowe jest tworzone losowo w funkcji:
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@ -51,17 +34,14 @@ Dane testowe jest tworzone losowo w funkcji:
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order.append(tmpr[0])
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order.append(tmpr[0])
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order.append('order')
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order.append('order')
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return order
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return order
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### Implementacja
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### Implementacja
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####Drzewo:
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####Drzewo:
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Klasy:
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Klasy:
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Klasa Question
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#####Question
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#####Question
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class Queestion:
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class Queestion:
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def __init__(self, col, value):
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def __init__(self, col, value):
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@ -73,7 +53,7 @@ Klasy:
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def __repr__(self):
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def __repr__(self):
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#just to print
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#just to print
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Klasa Node
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#####Node
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#####Node
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class Decision_Node():
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class Decision_Node():
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#contain the question and child nodes
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#contain the question and child nodes
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@ -91,7 +71,6 @@ Klasy:
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### Biblioteki
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### Biblioteki
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* concepts
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* random
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* random
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* numpy
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* numpy
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