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For our project, we are working on a dataset with relatively fewer variables (
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Hey hi @lmcinnes
First of all, thx for this method. It working so well !
So I have a general question about using UMAP as a dimensionality reduction step in a prediction pipeline. We have a clas…
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pd.read_csv("../data/world_happiness.csv")
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(nllp) MacBook-Air-3:lnlp user$ python main.py tests/test_data/data.csv
Welcome to the NLLP CLI!
Loaded data from tests/test_data/data.csv
1. Run a Topic Model
2. Run an Optimization routine fo…
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```
The following is from a posting by Olivier Grisel. This is something we
should consider learning about and working on.
I wondered if you were aware of the recent developments around sparsity
p…
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QIIME currently only implements Principal Coordinate Analysis (PCoA) for dimensionality reduction and subsequent viewing with Emperor. While PCoA is a tried and true method within the metagenomic com…
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Dear Linnarson team,
First of all, thanks for the great dataset.
I was wondering, if there is any possibility to provide a loom file with dim reductions (PCA, tSNE)? Especially these dim reducti…
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EMPeror currently requires the eigenvalues and percent variation explained because these are important pieces of information in PCoA plots. However, in adding new algorithms to QIIME, specifically Ma…
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```
The following is from a posting by Olivier Grisel. This is something we
should consider learning about and working on.
I wondered if you were aware of the recent developments around sparsity
p…
-
I just realized that while the `dimensionality reduction widgets puts its results (e.g., `UMAP0` and `UMAP1`) in the features table, but for the cluster widget this somehow ends up in `layer.propertie…