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Training_​a_​Churn_​Predictor_​AutoML

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 / Data Preparation Train different models withAutoML Evaluation Apply and score Model Churn Prediction - TrainingThis workflow is an example of how to train a basic machine learning model for a churn prediction task, using a Decision Tree algorithm. class = churn80%vs. 20%colorby churnarea codeand churn ->StringAuCCalls dataContract dataperformancescoringapply best ML pipelineAutoML Partitioning Color Manager Number To String ROC Curve Excel Reader CSV Reader Scorer Joiner Workflow Executor 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 / Data Preparation Train different models withAutoML Evaluation Apply and score Model Churn Prediction - TrainingThis workflow is an example of how to train a basic machine learning model for a churn prediction task, using a Decision Tree algorithm. class = churn80%vs. 20%colorby churnarea codeand churn ->StringAuCCalls dataContract dataperformancescoringapply best ML pipelineAutoML Partitioning Color Manager Number To String ROC Curve Excel Reader CSV Reader Scorer Joiner Workflow Executor

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Created by: rosy
Created at: 2015-04-23
On NodePit since: 2022-11-08
Last update: 2024-04-27
Created with KNIME version: v4.6.3
Tags: Customer IntelligenceCIchurndecision treePracticing Data Science

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