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38 lines
1.5 KiB
38 lines
1.5 KiB
1. Objective: We want to predict whether a customer will change providers (denoted as Churn) based on the usage pattern of customers.
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2. License: Free to use, with citation request.
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3. Data Source: http://www.sgi.com/tech/mlc/db/churn.all
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4. DataSet Info: This is a dataset artificial based on claims similar to real world.
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5. Field Meanings:
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A. State: The State where the customer is from.
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B. Account Length: How long the account has been active.
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C. Area Code: Area Code.
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D. Phone: Phone number.
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E. Int'l Plan: Indicate whether the customer has International Plan.
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F. VMail Plan: Indicate whether the customer has Voice Mail Plan.
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G. VMail Message: Number of voice mail messages.
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H. Day Mins: Total day minutes.
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I. Day Calls: Total day calls.
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J. Day Charge: Total day charge.
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K. Eve Mins: Total evening minutes.
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L. Eve Calls: Total evening calls.
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M. Eve Charge: Total evening charge.
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N. Night Mins: Total night minutes.
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O. Night Calls: Total night calls.
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P. Night Charge: Total night charge.
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Q. Intl Mins: Total international minutes.
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R. Intl Calls: Total international calls.
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S. Intl Charge: Total international charge.
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T. CustServ Calls: Numbers of calls to customer service.
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U. Churn?: Whether the customer choose to churn or not.
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6. Parameter Selection:
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A. Dashboard Usage: Predict Categorical Fields
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Settings:
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1) Search command: | inputlookup churn.csv
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2) Field to predict: Churn?
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3) Fields to use for predicting: CustServ Calls, Day Mins, Eve Mins, Int'l Plan, Intl Calls, Intl Charge, Intl Mins, Night Charge, Night Mins, VMail Plan
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