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transpose dimensions of X in BayesNetwork

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This commit is contained in:
Ricardo Montañana Gómez
2023-07-08 01:13:29 +02:00
parent 8a9c86a22d
commit 260997c872
2 changed files with 879 additions and 332 deletions
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1199
bayesclass/BayesNetwork.cpp
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12
bayesclass/BayesNetwork.pyx
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@@ -25,15 +25,19 @@ cdef class BayesNetwork:
def __dealloc__(self):
del self.thisptr
def fit(self, X, y, features, className):
X_ = [X[:, i] for i in range(X.shape[1])]
features_bytes = [x.encode() for x in features]
self.thisptr.fit(X, y, features_bytes, className.encode())
self.thisptr.fit(X_, y, features_bytes, className.encode())
return self
def predict(self, X):
return self.thisptr.predict(X)
X_ = [X[:, i] for i in range(X.shape[1])]
return self.thisptr.predict(X_)
def predict_proba(self, X):
return self.thisptr.predict_proba(X)
X_ = [X[:, i] for i in range(X.shape[1])]
return self.thisptr.predict_proba(X_)
def score(self, X, y):
return self.thisptr.score(X, y)
X_ = [X[:, i] for i in range(X.shape[1])]
return self.thisptr.score(X_, y)
def addNode(self, name, states):
self.thisptr.addNode(str.encode(name), states)
def addEdge(self, source, destination):