Classification Dataset
Dataset Description
Column Descriptions:
- age (int): The age of the individual.
- gender (string): The gender of the individual, either 'Male' or 'Female'.
- occupation (string): The occupation of the individual.
- education_level (string): The highest level of education attained by the individual, such as 'High School', 'Associate's', 'Bachelor's', 'Master's', or 'Doctoral'.
- marital_status (string): The marital status of the individual, either 'Single' or 'Married'.
- income (int): The annual income of the individual in dollars.
- credit_score (int): The credit score of the individual, ranging from 300 to 850.
loan_status (string): The target variable, indicating whether the loan application was 'Approved' or 'Denied'.
This dataset contains various demographic and financial features that could be used to build a classification model for predicting loan approval or denial. The loan_status column serves as the target variable for the classification task.
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Fur Banning
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