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README.md
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This dataset is designed to assist in predicting a customer's propensity to purchase various products within a month following the reporting date. The dataset includes anonymized historical data on transaction activity, dialog embeddings, and geo-activity for some bank clients over 12 months.
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Reduced dataset version is avaliable as [MBD-mini](https://huggingface.co/datasets/ai-lab/MBD-mini). The mini MBD dataset contains a reduced subset of the data, making it easier and faster to work with during the development and testing phases. It includes a smaller number of clients and a shorter time span but maintains the same structure and features as the full dataset. MBD-mini has data based on 10% of unique clients listed in MBD.
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# Data
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The dataset consists of anonymized historical data, which contains the following information for some of the Bank's clients over 12 months:
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```
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client_split Desc: Splitting clients into folds
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|-- client_id: str Desc: Client id
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|-- fold: int
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detail
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|-- client_id: str Desc: Client id
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|-- event_time: timestamp Desc: Dialog's date
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|--embedding: array float Desc: Dialog's embeddings
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|-- fold: int
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|-- geo Desc: Geo activity
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|-- client_id: str Desc: Client id
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|-- geohash_4: int Desc: Geohash level 4
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|-- geohash_5: int Desc: Geohash level 5
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|-- geohash_6: int Desc: Geohash level 6
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|-- trx Desc: Transactional activity
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|-- client_id: str Desc: Client id
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|-- event_time: timestamp Desc: Transaction's date
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|-- src_type22: int Desc: Clarifying feature 2 for sender
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|-- src_type31: int Desc: Feature 3 for sender
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|-- src_type32: int Desc: Clarifying feature 3 for sender
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ptls Desc: Data is similar with detail but in pytorch-lifestream format https://github.com/dllllb/pytorch-lifestream
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|-- dialog Desc: Dialogue embeddings
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|-- client_id: str Desc: Client id
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|-- event_time: Array[timestamp] Desc: Dialog's date
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|-- embedding: Array[float] Desc: Dialog's embedding
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|-- fold: int
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|-- geo Desc: Geo activity
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|-- client_id: str Desc: Client id
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|-- geohash_4: Array[int] Desc: Geohash level 4
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|-- geohash_5: Array[int] Desc: Geohash level 5
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|-- geohash_6: Array[int] Desc: Geohash level 6
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|-- trx Desc: Transactional activity
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|-- client_id: str Desc: Client id
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|-- event_time: Array[timestamp] Desc: Transaction's date
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|-- src_type22: Array[int] Desc: Clarifying feature 2 for sender
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|-- src_type31: Array[int] Desc: Feature 3 for sender
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|-- src_type32: Array[int] Desc: Clarifying feature 3 for sender
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targets
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|-- mon: str Desc: Reporting month
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|-- trans_count: int Desc: Number of transactions
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|-- diff_trans_date: int Desc: Time difference between transactions
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|-- client_id: str Desc: Client id
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|-- fold: int
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```
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This dataset is designed to assist in predicting a customer's propensity to purchase various products within a month following the reporting date. The dataset includes anonymized historical data on transaction activity, dialog embeddings, and geo-activity for some bank clients over 12 months.
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Reduced dataset version is avaliable as [MBD-mini](https://huggingface.co/datasets/ai-lab/MBD-mini). The mini MBD dataset contains a reduced subset of the data, making it easier and faster to work with during the development and testing phases. It includes a smaller number of clients and a shorter time span but maintains the same structure and features as the full dataset. MBD-mini has data based on 10% of unique clients listed in MBD.
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To get a balanced version of the dataset, you can use the field is_balanced == 1
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# Data
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The dataset consists of anonymized historical data, which contains the following information for some of the Bank's clients over 12 months:
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```
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client_split Desc: Splitting clients into folds
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|-- client_id: str Desc: Client id
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|-- is_balanced: int Desc: Balanced sample status
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|-- fold: int
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detail
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|-- client_id: str Desc: Client id
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|-- event_time: timestamp Desc: Dialog's date
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|--embedding: array float Desc: Dialog's embeddings
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|-- is_balanced: int Desc: Balanced sample status
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|-- fold: int
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|-- geo Desc: Geo activity
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|-- client_id: str Desc: Client id
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|-- geohash_4: int Desc: Geohash level 4
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|-- geohash_5: int Desc: Geohash level 5
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|-- geohash_6: int Desc: Geohash level 6
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|-- is_balanced: int Desc: Balanced sample status
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|-- trx Desc: Transactional activity
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|-- client_id: str Desc: Client id
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|-- event_time: timestamp Desc: Transaction's date
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|-- src_type22: int Desc: Clarifying feature 2 for sender
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|-- src_type31: int Desc: Feature 3 for sender
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|-- src_type32: int Desc: Clarifying feature 3 for sender
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|-- is_balanced: int Desc: Balanced sample status
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ptls Desc: Data is similar with detail but in pytorch-lifestream format https://github.com/dllllb/pytorch-lifestream
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|-- dialog Desc: Dialogue embeddings
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|-- client_id: str Desc: Client id
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|-- event_time: Array[timestamp] Desc: Dialog's date
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|-- embedding: Array[float] Desc: Dialog's embedding
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|-- is_balanced: int Desc: Balanced sample status
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|-- fold: int
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|-- geo Desc: Geo activity
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|-- client_id: str Desc: Client id
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|-- geohash_4: Array[int] Desc: Geohash level 4
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|-- geohash_5: Array[int] Desc: Geohash level 5
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|-- geohash_6: Array[int] Desc: Geohash level 6
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|-- is_balanced: int Desc: Balanced sample status
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|-- trx Desc: Transactional activity
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|-- client_id: str Desc: Client id
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|-- event_time: Array[timestamp] Desc: Transaction's date
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|-- src_type22: Array[int] Desc: Clarifying feature 2 for sender
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|-- src_type31: Array[int] Desc: Feature 3 for sender
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|-- src_type32: Array[int] Desc: Clarifying feature 3 for sender
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|-- is_balanced: int Desc: Balanced sample status
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targets
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|-- mon: str Desc: Reporting month
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|-- trans_count: int Desc: Number of transactions
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|-- diff_trans_date: int Desc: Time difference between transactions
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|-- client_id: str Desc: Client id
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|-- is_balanced: int Desc: Balanced sample status
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|-- fold: int
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```
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