Python package for thresholded partial least squares
Project description
TPLSp 1.1.0
Python Package for using Thresholded Partial Least Squares (TPLS) for big data regression and classification. It is developed with whole-brain neuroimaging (fMRI) MVPA predictors in mind. TPLS uses analytical calulations of partial least squares to dramatically speed-up the training of models with large number of features (~millions).
You can install from pypi using pip: pip install --upgrade TPLSp
Look under the examples folderin github for step-by-step tutorial on how to use TPLS. https://github.com/sangillee/TPLSp
Citation: Lee, S., Bradlow, E. T., & Kable, J. W. (2022). Fast construction of interpretable whole-brain decoders. Cell Reports Methods, 100227.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file TPLSp-1.1.0.tar.gz.
File metadata
- Download URL: TPLSp-1.1.0.tar.gz
- Upload date:
- Size: 8.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.10.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9f6f3797ef59f8e38468d68d8e9f992231d3f2f68325a362628b7095bf5f16af
|
|
| MD5 |
14a44f7918ddebc9baaa445467fd7a27
|
|
| BLAKE2b-256 |
e7c0b60571834e6607b9b88c78ffb72aaf8a24646a97c4f24df4d8c4ffa70563
|
File details
Details for the file TPLSp-1.1.0-py3-none-any.whl.
File metadata
- Download URL: TPLSp-1.1.0-py3-none-any.whl
- Upload date:
- Size: 8.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.10.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f5475b43189953625886526bce83070eecab0931f7758f38733e393a89b3a7fc
|
|
| MD5 |
032dc68b6ba001745cf0d175075c8cd9
|
|
| BLAKE2b-256 |
4b13769e64395b3ee2f7711033b5e117fa19fc7ce088db331a6bfd70f7dda349
|
