cls = Kfda(kernel='rbf', n_components=3)
clf = cls.fit_transform(X_train, y_train)
TypeError: np.matrix is not supported. Please convert to a numpy array with np.asarray.

Although I have converted the data to np.array, he still reminded me that I do not support np.matrix, Please convert to a numpy array with np.array.
These codes used to work normally, but now they keep reporting this error. I look forward to your help to solve this problem. Thank you.

Hi there,

Thank you for providing this tool. However, when I test the tool using simple input, I got an error:

cls = Kfda(kernel='rbf', n_components=2)
train_embeddings = cls.fit_transform(X, y)

TypeError Traceback (most recent call last)
in
1 cls = Kfda(kernel='rbf', n_components=2)
----> 2 train_embeddings = cls.fit_transform(X, y)

~/opt/anaconda3/lib/python3.7/site-packages/sklearn/base.py in fit_transform(self, X, y, **fit_params)
554 else:
555 # fit method of arity 2 (supervised transformation)
--> 556 return self.fit(X, y, **fit_params).transform(X)
557
558

~/opt/anaconda3/lib/python3.7/site-packages/kfda/kfda.py in transform(self, X)
115 projected onto the fisher directions.
116 """
--> 117 check_is_fitted(self)
118 return pairwise_kernels(
119 X, self.X_, metric=self.kernel, **self.kwds

TypeError: check_is_fitted() missing 1 required positional argument: 'attributes'