kmds-modeling 0.2.1

KMDS modeling pipeline package for KMDS lifecycle and model selection.

KMDS Modeling

kmds-modeling is a lightweight supporting package for KMDS modeling workflows. It provides the runtime plumbing, evaluation orchestration, and artifact export utilities needed to bridge KMDS feature outputs and production-ready model assets.

Overview

• Supports KMDS workspace modeling without embedding domain-specific business logic.
• Provides a generic ExperimentRunner engine for cross-validation, transformer orchestration, and candidate model evaluation.
• Includes a CLI for standard evaluation and production export flows.
• Keeps workspace-specific examples and artifacts outside the installable package.

Key Features

• Config-driven modeling pipeline via modeling_config.yaml
• Safe cross-validation with fold-specific transformer fitting
• Uniform candidate wrapper support for any model implementation
• Export of serialized model weights, feature pipeline, and metadata
• Path coordination for KMDS workspace layout handling

Installation

pip install kmds-modeling

CLI

The package exposes a command-line interface for model evaluation and export.

kmds-modeling evaluate --config /path/to/modeling_config.yaml
kmds-modeling export --config /path/to/modeling_config.yaml

Configuration

The package expects a YAML configuration file that defines:

• project settings such as name, version, and target variable
• data settings including working directory and index column
• experiment_settings for cross-validation and metrics
• candidates listing candidate models and their hyperparameters
• production_target for champion export paths

The PathCoordinator resolves workspace-relative paths and ensures the package operates on KMDS-generated modeling artifacts.

Recommended Workflow

1. Generate feature-engineered data with KMDS upstream tools such as kmds-featurization.
2. Author a modeling_config.yaml with the correct workspace layout and candidate definitions.
3. Run kmds-modeling evaluate to compare candidate models and generate a leaderboard.
4. Select the champion candidate and run kmds-modeling export to produce model artifacts.

Project Structure

• src/kmds_modeling/ — installable package source
• src/kmds_modeling/cli.py — CLI entrypoint
• src/kmds_modeling/core/runner.py — evaluation and export orchestration
• src/kmds_modeling/core/path_coordinator.py — workspace path resolution
• src/kmds_modeling/core/notebook_utils.py — notebook-friendly utilities

Contribution Notes

• Keep core modeling logic generic and focused on KMDS pipeline support.
• Add workspace-specific examples or experimental workflows outside the installable source tree.
• Avoid coupling the package to any single KMDS project domain.