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Fit LDA to all tweets. Infer topic distribution for each user. Compare average \# of topics
(or entropy) for high and low follower count users.
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In cases where you know in advance some of the topics/meta-features in your data, and you still wish to run NMF to find additional topics/meta-features (W matrix) and the topics/meta-features importan…
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Hi,
I've just seen that the repo has been updated to reflect changes till now. I have several questions on the way forward.
* Are we going to make an application for this? What if someone want…
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Hi,
Thanks for developing this package! I encounter an error when running fit_factorization.
I am using some scRNA-seq data with 11275 genes and 1000 cells (a random subset of all cells). The data i…
zji90 updated
4 years ago
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I was doing some tests with the nnlm function hoping it would be faster than the inbuilt nnls R function, but if I try with a 200 x 1000 covariate matrix x and a univariate outcome variable y it turns…
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# 概要
embedding関係の総論的なディスカッションスペース
今後の調査方針なども含めて議論しましょう。
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Non-Method Features to add:
- [x] Rotation Matrix for PCA and ICA
- [ ] mean and std vectors from PCA, ICA and PCA L1
- [ ] Eigenvalues
- [ ] kernel Matrices for kPCA
- [ ] update documentation f…
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Hi, I'm getting the error below when running the factorize step. I presume there's some confusion about when to input all features or 2000 over-dispersed features. Can you advise?
```
Cell In[9], …
whtns updated
3 months ago
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Adam Calhoun posted some simple analyses of the Cosyne Abstracts across time. Maybe they're inspiring for the kinds of things we'd want to do?
https://neuroecology.wordpress.com/2016/02/23/cosyne2016…
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- posting at specific times of the day/week
+ [ ] binary was a tweet posted last Friday,
+ [ ] % messages on last X Fridays (dependent on aggregation window),
+ [ ] % X last Fridays with at…