abidlabs contrastive issues

abidlabs / contrastive

Contrastive PCA

MIT License

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issues

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cPCA reverse transform

#26 hliu56 opened 2 weeks ago
0
Adding greater visibility of plots, as well as scree plots for greater comparison ability

#25 patjiang opened 1 month ago
1
Update __init__.py

#24 patjiang closed 1 month ago
0
trying to understand how this is unsupervised learning/theory behind

#23 klai001 opened 8 months ago
0
Switch sklearn for scikit-learn package.

#22 jzazo closed 1 year ago
0
Problem installing

#21 RobertoDF closed 1 year ago
4
sign mod on all components

#20 jkobject opened 3 years ago
0
No plotting of background data

#19 ideasbyjin opened 3 years ago
1
Update __init__.py

#18 gabriel-santanna closed 3 years ago
0
Projected data is a matrix of complex numbers

#17 toosi opened 3 years ago
0
Reverse cPCA

#16 PietroD opened 3 years ago
0
What is the legend argument used for?

#15 krassowski opened 4 years ago
0
Piping with .fit().transform() not possible

#14 krassowski opened 4 years ago
0
ValueError: n_components=1000 must be between 0 and min(n_samples, n_features)=100 with svd_solver='full'

#13 krassowski opened 4 years ago
1
LA.eig(sigma) gives complex eigenvalues for symmetrical sigma

#12 tamkaho opened 4 years ago
0
'NameError: name 'cpca_alpha' is not defined' while using Kernel cPCA

#11 tauhidstanford opened 5 years ago
0
Why do you adjust the sign here?

#10 dbeach24 closed 5 years ago
1
Return alphas as option to CPCA() class

#9 gtiao closed 5 years ago
2
Mice protein experiment does not work

#8 Periodinan closed 6 years ago
1
TypeError: 'numpy.float64' object cannot be interpreted as an integer

#7 edifice1989 closed 6 years ago
1
added namespace check in __init__.py

#6 drakeeee closed 6 years ago
0
How to get the top cPCA components?

#5 vyraun closed 6 years ago
2
Example from quick test does not work

#4 ndaniel closed 7 years ago
2
Ability to specify the number of PCs to return

#3 kieran-mace closed 7 years ago
2
Unclear how to format input matrices

#2 kieran-mace closed 7 years ago
1
Slides from talk?

#1 AvantiShri closed 7 years ago
1

abidlabs / contrastive

issues

cPCA reverse transform

Adding greater visibility of plots, as well as scree plots for greater comparison ability

Update init.py

trying to understand how this is unsupervised learning/theory behind

Switch sklearn for scikit-learn package.

Problem installing

sign mod on all components

No plotting of background data

Update init.py

Projected data is a matrix of complex numbers

Reverse cPCA

What is the legend argument used for?

Piping with .fit().transform() not possible

ValueError: n_components=1000 must be between 0 and min(n_samples, n_features)=100 with svd_solver='full'

LA.eig(sigma) gives complex eigenvalues for symmetrical sigma

'NameError: name 'cpca_alpha' is not defined' while using Kernel cPCA

Why do you adjust the sign here?

Return alphas as option to CPCA() class

Mice protein experiment does not work

TypeError: 'numpy.float64' object cannot be interpreted as an integer

added namespace check in init.py

How to get the top cPCA components?

Example from quick test does not work

Ability to specify the number of PCs to return

Unclear how to format input matrices

Slides from talk?