Coordinate Rotation for Spatial Interpolation
Project description
crospint: Coordinate Rotation for Spatial Interpolation
This package provides lightweight utilities and scikit-learn-compatible transformers to build efficient machine learning pipelines for spatio-temporal interpolation with tree-based ensemble methods. This package also contains functions and classes uses to model housing prices at the national scale (see Meslin [2026]).
This package has three distinctive features:
- It offers a native
sklearn.Pipelineintegration; - It uses
polarsfor fast feature engineering but is also fullypandas-compatible to simplify use with other ML libraries; - It is agnostic to the algorithms used for interpolation (though is uses
lightgbmby default).
This package also contains functions and classes uses to model housing prices at the national scale (see Meslin [2026]).
Installation
Just execute uv add crospint or pip install crospint.
Basic use
To be completed
Notebooks
Two notebooks illustrate the valuation method describe in Meslin [2026]:
-
How to apply the conditional tail removal procedure
-
How to train price models at the national scale
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