Update README.md

README.md

@@ -41,9 +41,7 @@ The dataset can be utilized within a Bayesian framework to enhance the predictiv
 
 ## Dataset Structure
 
-Based on the output of the `summary()` function for your dataset, here's a description of the dataset fields and additional information about the dataset structure:
-
-### Dataset Structure Description
+### Incidence Dataset Structure Description
 1. LTC Claim Incidence
 - **Group_Indicator**: Categorical variable indicating the group to which the policyholder belongs.
 - **Gender**: Categorical variable indicating the gender of the policyholder.
@@ -80,6 +78,22 @@ Based on the output of the `summary()` function for your dataset, here's a descr
 2. LTC Claim Termination
 
 
+### Termination Dataset Structure Description
+
+- **Gender**: Categorical variable indicating the gender of the policyholder.
+- **Incurred_Age_Bucket**: Categorical variable denoting the age range when the claim was incurred.
+- **Incurred_Year_Bucket**: Categorical variable indicating the year range when the claim was incurred.
+- **Claim_Type**: Categorical variable indicating the type of claim made.
+- **Region**: Categorical variable indicating the geographical region of the policy.
+- **Diagnosis_Category**: Categorical variable providing the category of diagnosis related to the claim.
+- **Claim_Duration**: Categorical variable representing the duration that the claim has been active.
+- **Exposure**: Numeric variable indicating the measure of risk that the insurer has been exposed to for the policy.
+- **Deaths**: Numeric variable indicating the number of deaths among the policyholders.
+- **Recovery**: Numeric variable indicating the number of policyholders who have recovered.
+- **Terminations**: Numeric variable indicating the number of policy terminations.
+- **Benefit_Expiry**: Numeric variable indicating the number of terminations due to benefits reaching their expiration date.
+- **Others_Terminations**: Numeric variable indicating the number of terminations due to other unspecified reasons.
+
 ## Dataset Creation
 
 ### Curation Rationale