This release is a pre-release and may not be stable for production use.
Model
This repository contains the implementation of the MetaRisk Model Infrastructure.
Related Document: Revisiting_MetaRisk_V2.pdf
Quality-aware observations
OrganAgeMetaRisk configures each observation channel as a (value_column, quality_column) pair. For an available
channel, the observation standard deviation is phi_group / sqrt(Q), where Q is the raw, dimensionless quality score
in [MIN_OBSERVATION_QUALITY, 1]. Q=1 is the reference-quality anchor for phi_group.
Quality columns are required in every dataframe passed to fit(), predict(), or log_likelihood(). Quality is not
included in observation preconditioning and does not add a likelihood correction. If preprocessing cannot provide a
valid score for an observation, it must mark that observation missing before passing the dataframe to the model.
Models are persisted as format-v3 payloads. Older v1/v2 payloads are rejected by metarisk.models.load() and must be
converted explicitly with metarisk.utils.migrate_model_payload(..., quality_column_mapping=...) before they can be
saved and loaded as v3; quality-column names are never inferred.
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Release files for metarisk 1.7.0rc1
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|---|---|---|---|---|
| metarisk-1.7.0rc1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 175.4 kB
Release files / metarisk-1.7.0rc1.tar.gz
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