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justKnimeit-24

justKnimeit-24
Challenge 24: Modeling Churn Predictions - Part 2Description: Just like in last week’s challenge, a telecom company wants you to predict which customers are going to churn (that is, going tocancel their contracts) based on attributes of their accounts. One of your colleagues said that she was able to achieve a bit over 95% accuracyfor the test data without modifying the training data at all, and using all given attributes exactly as they are. Again, the target class to be predictedis Churn (value 0 corresponds to customers that do not churn, and 1 corresponds to those who do). What model should you train over thetraining dataset to obtain this accuracy over the test dataset? Can this decision be automated? execute up-streambefore configurationtraining datasettest datasetAcc: %95,05 AutoML CSV Reader CSV Reader Workflow Executor Scorer Challenge 24: Modeling Churn Predictions - Part 2Description: Just like in last week’s challenge, a telecom company wants you to predict which customers are going to churn (that is, going tocancel their contracts) based on attributes of their accounts. One of your colleagues said that she was able to achieve a bit over 95% accuracyfor the test data without modifying the training data at all, and using all given attributes exactly as they are. Again, the target class to be predictedis Churn (value 0 corresponds to customers that do not churn, and 1 corresponds to those who do). What model should you train over thetraining dataset to obtain this accuracy over the test dataset? Can this decision be automated? execute up-streambefore configurationtraining datasettest datasetAcc: %95,05 AutoML CSV Reader CSV Reader Workflow Executor Scorer

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Created by: eyilmaz35
Created at: 2022-07-07
On NodePit since: 2022-07-08
Last update: 2024-04-26
Created with KNIME version: v4.5.2
Tags: justKnimeit-24

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