Datasets:
X_train listlengths 400 400 | y_train listlengths 400 400 | X_test listlengths 100 100 | y_test listlengths 100 100 | data_id stringlengths 13 13 | graph_id stringlengths 14 14 | target_idx int64 0 19 | dataset_idx int64 0 0 | n_train int64 400 400 | n_test int64 100 100 | n_features int64 9 19 | adjacency_matrix listlengths 10 20 | feature_mask listlengths 9 19 | selection_method stringclasses 1
value | parents listlengths 9 19 | children listlengths 9 19 | spouses listlengths 9 19 | scm dict | environment dict | graph_meta dict |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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End of preview. Expand in Data Studio
Dataset
Configuration
dataset_name: final-dataset
graphs_path: hf://CSE472-blanket-challenge/final-graphs
output_path: data/datasets/${dataset_name}
n_samples: 500
n_datasets: 1
scm_type: linear, nonlinear
coeff_range: 1.0
noise_std: 0.5
env_type: iid, covariate, label
projection: pca
shift_mean: 0.8
shift_std: 0.2
train_fraction: 0.8
seed: 42
overwrite: true
Load data
from datasets import load_dataset
develop = load_dataset("CSE472-blanket-challenge/final-dataset", 'develop', split='train')
submit = load_dataset("CSE472-blanket-challenge/final-dataset", 'submit', split='train')
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