Factual package intelligence from PyPI

model-confidence-set 0.1.3 package intelligence

model-confidence-set provides a Python implementation of the Model Confidence Set (MCS) procedure (Hansen, Lunde, and Nason, 2011), a statistical method for comparing and selecting models based on their performance.

pip install model-confidence-set

Current version
0.1.3
Python requirement
Not declared
License
MIT
Distribution type
Pure Python wheel
Release files
2 (1 wheels, 1 source)
Download size
13.1 KiB
Release history
4 releases with files
Median release cadence
12 days

model-confidence-set dependencies

PyPI declares 4 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. numba >=0.59.0
  2. numpy >=1.26.4
  3. pandas >=2.2.1
  4. tqdm >=4.66.2

Compatibility and release files

model-confidence-set publishes 1 wheel and 1 source archive for version 0.1.3. Wheel platform tags: any.

No version-specific Python classifiers are declared.

Metadata completeness

PyPI does not currently declare: Python requirement. PyDeps marks these fields as unknown instead of guessing values.

Release activity and sources

PyPI lists 4 releases with files. The first dated release is ; 4 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .