Registry / ai-ml / scikit-dimension

scikit-dimension

library0.3.4pypypiunverified

scikit-dimension is a Python module for intrinsic dimension estimation built according to the scikit-learn API. It provides estimators for global and local intrinsic dimension, supporting methods like MLE, DANCo, kNN, and others. Current version 0.3.4 is released under the 3-Clause BSD license. Release cadence is irregular.

ai-ml

pip install scikit-dimension

github ↗package ↗

INSTALL

IMPORT

SIG · SCIKIT-DIMENSION

scikit-dimension

ai-mlpythonv0.3.4

Install

13.2s avg

Import

—

Disk

465MB

Pass rate

5/ 10

Env Coverage5 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.3.4 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

build_error

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 13.2s · import 0.000s · 458MB

465MB installed

● package 465MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

MLE

✓ from skdim import MLE

✗ from skdim.id import MLE

Basic usage of MLE estimator on random data.

from skdim.id import MLE import numpy as np # Generate synthetic data X = np.random.rand(100, 10) # Estimate intrinsic dimension mle = MLE() dim = mle.fit_transform(X) print('Estimated dimension:', dim)

Debug

Known issues

breakingIn v0.3, the `predict` method was changed to `transform`. Code using `predict` will break.

fix

Replace `.predict(X)` with `.transform(X)` or use `fit_transform(X)`.

affects: <0.3

gotchaThe kNN estimator class is named `kNN` (lowercase k), not `KNN`. Importing `KNN` raises ImportError.

fix

Use `from skdim.id import kNN`.

affects: all

gotchaSome estimators (eg MLE, DANCo) may return negative values if the data is not preprocessed. Intrinsic dimension must be non-negative.

fix

Ensure input data is scaled/normalized appropriately, and consider using the `denoising` parameter if available.

affects: all

deprecatedThe 'local' keyword argument in some estimators may be deprecated in future versions. Prefer using the dedicated `Local` or `Global` wrapper classes.

fix

Use `from skdim.local import ...` for local estimators, or check the documentation for the recommended API.

affects: >=0.3

Upgrade

Version history

0.3.4latest on PyPI · released Mar 11, 2024

Audit

Dependencies

scikit-learnrequiredcore dependency, API and estimator interface

numpyrequirednumerical computations

Agent activity

19 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/j-bac/scikit-dimension ↗

packagehttps://pypi.org/project/scikit-dimension/ ↗