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01_​Training_​a_​Churn_​Predictor

Training a Churn Predictor
Read Data Contract Data Calls Data Conversions Churn and Area Code to String Color Churn 0 -> Blue 1 -> Red Partitioning 80% training 20% testing Pre-processing Train Model Decision tree Save to PMML Evaluation Apply and score Model Churn Prediction: Training: This workflow is an example of how to build a basic PMML model for a churn prediction using a Decision Tree algorithm. 80%vs. 20%colorby churnclass = churnarea codeand churn ->StringCalls datacontract data Partitioning Decision TreePredictor Color Manager Joiner Equal Size Sampling DecisionTree Learner Number To String ROC Curve Scorer Excel Reader PMML Writer CSV Reader Read Data Contract Data Calls Data Conversions Churn and Area Code to String Color Churn 0 -> Blue 1 -> Red Partitioning 80% training 20% testing Pre-processing Train Model Decision tree Save to PMML Evaluation Apply and score Model Churn Prediction: Training: This workflow is an example of how to build a basic PMML model for a churn prediction using a Decision Tree algorithm. 80%vs. 20%colorby churnclass = churnarea codeand churn ->StringCalls datacontract data Partitioning Decision TreePredictor Color Manager Joiner Equal Size Sampling DecisionTree Learner Number To String ROC Curve Scorer Excel Reader PMML Writer CSV Reader

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Created by: rosy
Created at: 2015-04-23
On NodePit since: 2021-03-08
Last update: 2024-11-21
Created with KNIME version: v4.3.1
Tags: Customer IntelligenceCIchurn

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