Datasets:
seed int64 | accounts_num int64 | num_banks int64 | laundering_ratio float64 | wallet_id dict | wallet_type dict | wallet_level dict | wallet_open_date dict | wallet_open_cert_expire_offset_days dict | bank_code_prefixes list | normal_init_balance_mixture list | abnormal_init_balance_mixture list | wallet_level_balance_caps dict | region_code dict | distribution_based_generation dict | output_csv string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1,234 | 1,000 | 10 | 0.05 | {
"length": 14,
"numeric_only": true,
"no_leading_zero": true
} | {
"options": [
1,
2,
3
],
"probs": [
0.4,
0.4,
0.2
]
} | {
"options": [
1,
2,
3,
4
],
"probs": [
0.2,
0.05,
0.2,
0.55
]
} | {
"start": "2024-01-01T00:00:00",
"end": "2025-02-18T00:00:00"
} | {
"min": 365,
"max": 3650
} | [
"6220",
"6212",
"6213",
"6214",
"6215",
"6216",
"6217",
"6218",
"6219",
"6221"
] | [
{
"type": "point",
"value": 0.01,
"prob": 0.01,
"min": null,
"max": null,
"mu": null,
"sigma": null
},
{
"type": "point",
"value": 0.5,
"prob": 0.01,
"min": null,
"max": null,
"mu": null,
"sigma": null
},
{
"type": "uniform",
"value": null,
... | [
{
"type": "point",
"value": 0.01,
"prob": 0.01,
"min": null,
"max": null,
"mu": null,
"sigma": null
},
{
"type": "point",
"value": 0.5,
"prob": 0.01,
"min": null,
"max": null,
"mu": null,
"sigma": null
},
{
"type": "uniform",
"value": null,
... | {
"1": null,
"2": 5000000,
"3": 200000,
"4": 100000
} | {
"codes": [
"110000",
"310000",
"440100",
"440300",
"120000",
"320100",
"130100",
"140100",
"150100",
"210100",
"220100",
"230100",
"320200",
"330100",
"340100",
"350100",
"360100",
"370100",
"410100",
"420100",
"430100",
"450100... | {
"normal_wallet_distributions": {
"region_code": {
"normal_codes": [
"110000",
"310000",
"440100",
"440300",
"120000",
"320100",
"130100",
"140100",
"150100",
"210100",
"220100",
"230100",
"320200",
... | accounts.csv |
KnowFeat: Data, Features, and Provenance Cards
This repository contains the datasets, engineered features, domain knowledge inputs, and provenance cards for the KnowFeat paper on knowledge-guided automated feature engineering with large language models.
Repository Structure
data/
public/ # 7 public benchmark datasets (CSV)
simecny/ # Compressed transaction data (CSV.GZ)
inputs/
public_datasets/ # Domain knowledge JSONs for each dataset
simecny/ # Domain knowledge for transaction data
outputs/
features/ # Engineered feature CSV files produced by KnowFeat
provenance/ # Provenance cards (JSON + Markdown) documenting feature lineage
Data Description
- data/public/: Seven public tabular datasets used for evaluation (adult, bank_marketing, blood_transfusion, breast_w, credit_g, diabetes, heart).
- data/simecny/: Proprietary transaction dataset (compressed).
- inputs/: Domain knowledge files that guide the LLM-based feature engineering process.
- outputs/features/: The generated features from KnowFeat and baseline methods.
- outputs/provenance/: Provenance cards that record how each feature was created, including the LLM reasoning and statistical verification results.
Usage
These artifacts can be used to:
- Reproduce the experimental results from the KnowFeat paper
- Inspect the provenance of engineered features
- Benchmark new feature engineering methods against KnowFeat outputs
License
MIT
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