Customer Profile Classification Dataset

Description:
The "Customer Profile Classification Dataset" is a synthetic dataset created for the purpose of customer classification and profiling. It simulates a collection of customer profiles with a range of features that can be used for classification tasks, such as predicting customer behavior or segmentation.

Features:

1. Income: The customer's annual income in USD.
2. Age: The age of the customer.
3. Education: The highest level of education completed by the customer (categorical: High School, Bachelor, Master, PhD).
4. Credit_Score: The customer's credit score.
5. Years_with_Bank: The number of years the customer has been with the bank.
6. Transaction_Count: The number of transactions made by the customer.
7. Balance: The current account balance.
8. Loan_Approval_Amount: The amount approved for loans.
9. Credit_Card_Limit: The credit card limit for the customer.
10. Purchase_Frequency: The frequency of purchases made by the customer.
11. Customer_Satisfaction: A customer satisfaction rating (1 to 5, with 5 being the highest).
12. Online_Activity: Level of online activity, ranging from 0 (low) to 1 (high).

Target Variable:

• Target: A binary classification label (0 or 1) indicating a customer's classification for a particular task or analysis.

Purpose:
The dataset is designed to facilitate classification and predictive modeling tasks related to customer behavior. It can be used to explore patterns, build classification models, and perform customer segmentation based on various customer attributes.

Data Format:
The data is provided in a CSV (Comma-Separated Values) format with rows representing individual customer profiles and columns representing the features and the target variable.

Please note that this dataset is fictional and created for illustrative purposes. It is not based on real customer data, and any resemblance to real individuals or organizations is purely coincidental.