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License: MIT License
Code for the Metric Learning for Kernel Ridge Regression algorithm
License: MIT License
Hello, I would like to know if the dimensionality reduction data can be mapped back to the original space after using MLKR to reduce the dimensionality of the data? I've tried to map back to the original space without downgrading the dimension, but when I map the data back to the original space after downgrading, the number of columns in the L matrix is less than the number of rows and is irreversible? Can you give some comments on this?
Thank you for your help in advance!
TypeError Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_19020\1948509090.py in
----> 1 model = mlkrr.MLKRR(
2 verbose=True, shuffle_iterations=5,
3 max_iter_per_shuffle=20, krr_regularization = 1e-9,
4 size1=0.3, size2=0.7)
TypeError: init() got an unexpected keyword argument 'size1'
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