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Set k=2 in KDB to address memory problems

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This commit is contained in:
Ricardo Montañana Gómez
2023-01-06 14:29:22 +01:00
parent c21fd4849c
commit 9ba6c55d49
2 changed files with 2 additions and 3 deletions
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3
benchmark/Datasets.py
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@@ -216,8 +216,7 @@ class Datasets:
tuple (X, y) of numpy.ndarray tuple (X, y) of numpy.ndarray
""" """
discretiz = FImdlp(algorithm=0) discretiz = FImdlp(algorithm=0)
Xdisc = discretiz.fit_transform(X, y) return discretiz.fit_transform(X, y)
return Xdisc
def __iter__(self) -> Diterator: def __iter__(self) -> Diterator:
return Diterator(self.data_sets) return Diterator(self.data_sets)

2
benchmark/Models.py
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@@ -22,7 +22,7 @@ class Models:
return { return {
"STree": Stree(random_state=random_state), "STree": Stree(random_state=random_state),
"TAN": TAN(random_state=random_state), "TAN": TAN(random_state=random_state),
"KDB": KDB(k=3), "KDB": KDB(k=2),
"AODE": AODE(random_state=random_state), "AODE": AODE(random_state=random_state),
"Cart": DecisionTreeClassifier(random_state=random_state), "Cart": DecisionTreeClassifier(random_state=random_state),
"ExtraTree": ExtraTreeClassifier(random_state=random_state), "ExtraTree": ExtraTreeClassifier(random_state=random_state),