hoggorm
hoggorm is a Python package for explorative multivariate statistics in Python. It contains
PCA (principal component analysis)
PCR (principal component regression)
PLSR (partial least squares regression)
PLSR1 for single variable responses
PLSR2 for multivariate responses
matrix correlation coefficients RV, RV2 and SMI.
Unlike scikit-learn, which is an excellent python machine learning package focusing on classification and predicition, hoggorm rather aims at understanding and interpretation of the variance in the data. hoggorm also also contains tools for prediction.
Requirements
Make sure that Python 3.5 or higher is installed. A convenient way to install Python and many useful packages for scientific computing is to use the Anaconda distribution.
numpy >= 1.11.3
Installation
Install hoggorm easily from the command line from the PyPI - the Python Packaging Index.
pip install hoggormDocumentation
Documentation at Read the Docs
Jupyter notebooks with examples of how to use Hoggorm together with the complementary plotting package hoggormplot.
2 maintainers
Metadata
2 maintainers
Release files for hoggorm 0.13.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| hoggorm-0.13.3.tar.gz | 44.3 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hoggorm-0.13.3-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 92.0 kB
Release files / hoggorm-0.13.3.tar.gz
| Download URL | hoggorm-0.13.3.tar.gz |
|---|---|
| Size | 44.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
f1254d860f3024b2e6a2cecb2c0152f2010596235058781856c3a1a2f075c3b6
|
|
BLAKE2b-256 checksum How to use checksums |
0418d7a8fb6ca3e7b6a81bcca92a36b0b8e2abc42b0f72d6d23f8f6c4730bacd
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.13.0 pkginfo/1.4.2 requests/2.21.0 setuptools/40.6.3 requests-toolbelt/0.9.1 tqdm/4.28.1 CPython/3.7.1
|
Release files / hoggorm-0.13.3-py2.py3-none-any.whl
| Download URL | hoggorm-0.13.3-py2.py3-none-any.whl |
|---|---|
| Size | 47.6 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
ef94a1e8aa2ff3867b58c3d60fff29009ef329921074e05677fa5139fef623c6
|
|
BLAKE2b-256 checksum How to use checksums |
5b04f4076dc995100b6d66bbc4b552f5bd771f77eff8350ffe57d6b6c8d9e69b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.13.0 pkginfo/1.4.2 requests/2.21.0 setuptools/40.6.3 requests-toolbelt/0.9.1 tqdm/4.28.1 CPython/3.7.1
|
Security for hoggorm 0.13.3
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
