A package for estimating the intrinsic dimensionality of a dataset. Supports multiple estimation methods including Correlation Dimension, Nearest Neighbor Dimension, Packing Numbers, Geodesic Minimum Spanning Tree, Eigenvalue Analysis, Maximum Likelihood Estimation, and the newly added idPettis method. The idPettis method provides an innovative approach for dimensionality estimation, enhancing the package’s utility and accuracy in analyzing complex datasets.
Release files for IntrinsicDimEstimator 0.3.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| IntrinsicDimEstimator-0.3.2.tar.gz | 21.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| IntrinsicDimEstimator-0.3.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 40.7 kB
Release files / IntrinsicDimEstimator-0.3.2.tar.gz
| Download URL | IntrinsicDimEstimator-0.3.2.tar.gz |
|---|---|
| Size | 21.1 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.12.0
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Release files / IntrinsicDimEstimator-0.3.2-py3-none-any.whl
| Download URL | IntrinsicDimEstimator-0.3.2-py3-none-any.whl |
|---|---|
| Size | 19.6 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.12.0
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