Comments (5)
Hey there,
Your request is a good one. I'll make a note and try to get it done soon.
Cheers.
from prince.
I just implemented inverse_transform
for the PCA
class. I'm not exactly sure about how to go about this for CA, MCA and FAMD but I'm making steady progress. Feel free to contribute!
from prince.
Hey @MaxHalford, any news about implementing this nice feature ?
Thanks :) !
from prince.
Hi there @MaxHalford, will there be any updates on this? If not can you give some rough guidance on how to proceed with inverse transforming the data?
from prince.
Hey there! Actually I took a look and I have no idea on how to do this for FAMD, sorry :(. Actually I'm pretty sure you could write a scientific paper if you found a way haha.
from prince.
Related Issues (20)
- Unable to allocate memory HOT 4
- FAMD transform ValueError on qualitative data HOT 1
- 'MCA' object has no attribute '_check_is_fitted' with .transform HOT 2
- Not compatible with pandas 2.0.0 HOT 4
- Sklearn GridSearchCV: 'MCA' object has no attribute 'set_params' HOT 3
- Difficulty applying FMA with a group of categorical variables. HOT 1
- Handle_unknown in OneHotEncoder (FAMD) method HOT 5
- Information regarding Inverse MCA HOT 2
- MCA: plotting assumes raw dataset has already run get_dummies HOT 7
- prince.PCA vs. sklearn.decomposition.PCA? HOT 3
- UserWarning "pandas.DataFrame with sparse columns found" when running famd() HOT 1
- Feature idea: biplot HOT 2
- Compatibility with altair 5.0.x HOT 7
- Feature Idea: Weights HOT 3
- How to transform on new unseen test data? HOT 3
- CA.row_coordinates only works with pd.DataFrame HOT 5
- FAMD fit method not compatible with scikit-learn pipeline HOT 2
- MCA doesn't work with column transformers of sklearn HOT 2
- Bug in FAMD transform() HOT 1
- Support for sklearn Pipelines HOT 1
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