cpm skillA
cpm is agent-read markdown (skill) from cuhk-aim-group/neurodiscovery: Use this model skill whenever the user wants Connectome Predictive Modeling with fold-local functional-connectivity edge selection for classification or regression. Triggers include 'CPM', 'connectome predictive modeling', 'functional connectivity prediction', 'positive network', 'negative network', and 'edge selection'..
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What the file says
# CPM Skill ## Overview `cpm` is the canonical NeuroClaw implementation of Connectome Predictive Modeling. Edge selection is repeated independently inside every training fold. | Task | Input | Output | |---|---|---| | Classification | subject FC matrices/vectors | class and probability | | Regression | subject FC matrices/vectors | continuous prediction | --- ## Installation ```bash pip install numpy pandas scipy scikit-learn joblib ``` --- ## Workflows ### 1. Prepare data `connectomes.npz`: ```text X: [subjects, nodes, nodes] or [subjects, edges] subject_id: [subjects] ``` `labels.csv` contains the same subject IDs and a target column. ### 2. Regression ```bash python skills/cpm/scripts/train_reference.py \ --connectomes connectomes.npz \ --labels labels.csv \ --target cognitive_score \ --subject-col subject_id \ --task regression \ --p-threshold 0.01 \ --folds 5 \ --output-dir run_models_output/cpm ``` ### 3. Classification ```bash python skills/cpm/scripts/train_reference.py \ --connectomes connectomes.npz \ --labels labels.csv \ --target diagnosis \ --task classification \ --p-threshold 0.01 \ …
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How to install
mdr add cuhk-aim-group/neurodiscovery/cpm@git:20260825.cbd02ffmdr add cuhk-aim-group/neurodiscovery/cpm@sha256:67395d54be17a9abPin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
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Source
cuhk-aim-group/neurodiscovery · 91 stars · license MIT · pushed 2026-09-22 · branch main
API
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