├── .gitignore ├── 2020_materials ├── data │ ├── cpc_camcan_demographics.csv │ ├── cpc_camcan_demographics_nordan.csv │ ├── cpc_camcan_features.csv │ └── cpc_camcan_features_nordan.csv ├── tasks │ └── cpc_normative_modeling_instructions.ipynb └── tasks_key │ └── key_cpc_machinelearning.ipynb ├── README.md ├── data ├── Z_estimates.csv ├── Z_estimates_counts.csv ├── Z_long_format.csv ├── fcon1000_te.csv ├── fcon1000_te_Z.csv ├── fcon1000_tr.csv ├── nilearn_order.csv ├── phenotypes_lh.txt ├── phenotypes_rh.txt ├── phenotypes_sc.txt ├── sz_ct.npy ├── sz_labels.npy ├── sz_z.npy ├── task1_phenotypes.txt ├── test_data.csv └── train_data.csv ├── nm_utils.py ├── presentation ├── GPU.png ├── How_nm_compressed2020.pdf ├── Normative_Modeling_a_Framework_for_Clinical_Machinelearning.pdf ├── Runtime1.png ├── Runtime2.png ├── keyboard_pref.png ├── settings1.png └── settings2.png └── tasks ├── 1_fit_normative_models.ipynb ├── 2_apply_normative_models.ipynb ├── 3_Visualizations.ipynb └── 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