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Update README.md
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README.md
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@@ -75,7 +75,7 @@ The dataset can be utilized within a Bayesian framework to enhance the predictiv
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## Dataset Structure and Instances
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### Incidence Dataset Structure Description
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1. LTC Claim Incidence
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- **Group_Indicator**: Categorical variable indicating the group to which the policyholder belongs.
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- **Gender**: Categorical variable indicating the gender of the policyholder.
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- **Issue_Age_Bucket**: Categorical variable denoting the age range when the policy was issued.
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- **Count_HHC**: Numeric variable indicating the count of home health care claims.
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- **Count_Unk**: Numeric variable indicating the count of claims with unknown categorization.
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```
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{'Group_Indicator': 'Individual',
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- **Benefit_Expiry**: Numeric variable indicating the number of terminations due to benefits reaching their expiration date.
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- **Others_Terminations**: Numeric variable indicating the number of terminations due to other unspecified reasons.
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filtered_termination instances
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{'Gender': 'Male',
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'Incurred_Age_Bucket': '75-79',
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'Incurred_Year_Bucket': '2001-2002',
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'Terminations': '0',
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'Benefit_Expiry': '0',
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'Others_Terminations': '0'}
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-
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## Dataset Creation
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## Dataset Structure and Instances
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| 76 |
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### Incidence Dataset Structure Description
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1.0 LTC Claim Incidence
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- **Group_Indicator**: Categorical variable indicating the group to which the policyholder belongs.
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| 80 |
- **Gender**: Categorical variable indicating the gender of the policyholder.
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| 81 |
- **Issue_Age_Bucket**: Categorical variable denoting the age range when the policy was issued.
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- **Count_HHC**: Numeric variable indicating the count of home health care claims.
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- **Count_Unk**: Numeric variable indicating the count of claims with unknown categorization.
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### filtered_incidence instances
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```
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{'Group_Indicator': 'Individual',
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- **Benefit_Expiry**: Numeric variable indicating the number of terminations due to benefits reaching their expiration date.
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- **Others_Terminations**: Numeric variable indicating the number of terminations due to other unspecified reasons.
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### filtered_termination instances
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```
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{'Gender': 'Male',
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'Incurred_Age_Bucket': '75-79',
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'Incurred_Year_Bucket': '2001-2002',
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'Terminations': '0',
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'Benefit_Expiry': '0',
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'Others_Terminations': '0'}
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```
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## Dataset Creation
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