Prince MCA transformation error on new data

[EVAUTOAI]

I am using the newest version of prince (0.7.1), but this seems to be an issue on previous versions as well.

When I run the below code, i get no error.
mca = prince.MCA(n_components=2)
mca.fit(train_data)
x = mca.transform(train_data)

But when i try to apply the same model on test data:
y = mca.transform(test_data)

I get the below error:
_ValueError Traceback (most recent call last)
in
----> 1 y = mca.transform(test_data)
2 print(y)

/usr/local/anaconda3/envs/upe-pipeline/lib/python3.8/site-packages/prince/mca.py in transform(self, X)
48 if self.check_input:
49 utils.check_array(X, dtype=[str, np.number])
---> 50 return self.row_coordinates(X)
51
52 def plot_coordinates(self, X, ax=None, figsize=(6, 6), x_component=0, y_component=1,

/usr/local/anaconda3/envs/upe-pipeline/lib/python3.8/site-packages/prince/mca.py in row_coordinates(self, X)
36 if not isinstance(X, pd.DataFrame):
37 X = pd.DataFrame(X)
---> 38 return super().row_coordinates(pd.get_dummies(X))
39
40 def column_coordinates(self, X):

/usr/local/anaconda3/envs/upe-pipeline/lib/python3.8/site-packages/prince/ca.py in row_coordinates(self, X)
132
133 return pd.DataFrame(
--> 134 data=X @ sparse.diags(self.col_masses_.to_numpy() ** -0.5) @ self.V_.T,
135 index=row_names
136 )

/usr/local/anaconda3/envs/upe-pipeline/lib/python3.8/site-packages/scipy/sparse/base.py in rmatmul(self, other)
564 raise ValueError("Scalar operands are not allowed, "
565 "use '*' instead")
--> 566 return self.rmul(other)
567
568 ####################

/usr/local/anaconda3/envs/upe-pipeline/lib/python3.8/site-packages/scipy/sparse/base.py in rmul(self, other)
548 except AttributeError:
549 tr = np.asarray(other).transpose()
--> 550 return (self.transpose() * tr).transpose()
551
552 #######################

/usr/local/anaconda3/envs/upe-pipeline/lib/python3.8/site-packages/scipy/sparse/base.py in mul(self, other)
514
515 if other.shape[0] != self.shape[1]:
--> 516 raise ValueError('dimension mismatch')
517
518 result = self._mul_multivector(np.asarray(other))

ValueError: dimension mismatch_

I am not able to use the same transformation on new data, could you please help with this?

[MaxHalford]

Hello there 👋

I apologise for not answering earlier. I was not maintaining Prince anymore. However, I have just refactored the entire codebase. This refactoring should have fixed many bugs.

I don’t have time and energy to check if this fixes your issue, but there is a good chance it does. Feel free to reopen this issue if the problem persists after installing the new version — that is, version 0.8.0 and onwards.