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evaluator with evaluated data

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This commit is contained in:
Denys Seredenko
2024-11-05 16:27:32 +01:00
parent e5099b5acc
commit 4fe180d8bf
7 changed files with 1781 additions and 1729 deletions
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7
src/classes/decision_tree.py
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@@ -7,11 +7,12 @@ from classes.feature_vector import FeatureVector
class DecisionTree:
def __init__(self, children: dict = {}, parent: Self = None, concept: Concept = Concept.UNKNOWN, depth: int = 0) -> None:
def __init__(self, children: dict = {}, parent: Self = None, concept: Concept = Concept.UNKNOWN, depth: int = 0, cycles: int = 3) -> None:
self.children: dict = children # (number, DecisionTree)
self.parent: Self = parent
self.concept: Concept = concept
self.depth: int = depth
self.cycles: int = cycles
# TODO
@@ -55,11 +56,11 @@ class DecisionTree:
sub_decision_tree: Self = self.children[feature_value] # get sub decition tree for feature
sub_decision_tree._insert(vector)
except KeyError:
self.children.update({vector.features_list[self.depth]: DecisionTree(concept=vector.concept, parent=self, depth=self.depth+1, children={})})
self.children.update({vector.features_list[self.depth]: DecisionTree(concept=vector.concept, parent=self, depth=self.depth+1, children={}, cycles=self.cycles)})
def _finished(self, i: int, num_training_data: int):
# TODO implement proper finished condition
if i < num_training_data*3:
if i < num_training_data*self.cycles:
return False
return True

6
src/classes/learner.py
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@@ -80,9 +80,9 @@ class Learner:
def analyse(self, result, expectedConcept: Concept):
sorted_dict_result = {key: value for key, value in sorted(result.items(), reverse=True, key=lambda item: item[1])}
for key, amount in sorted_dict_result.items():
probability = (amount/self.k_paramter) * 100
print(f" Probability of {key} is {probability}%")
# for key, amount in sorted_dict_result.items():
# probability = (amount/self.k_paramter) * 100
# print(f" Probability of {key} is {probability}%")
if next(iter(sorted_dict_result)) == expectedConcept:
return 1