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HR attrition prediction (Julia)

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HR ATTRITION PREDICTION Scoring new data! Develop here your main analysis (wrap the nodes into metanodes to safe space and be tidy!) Set the cut-off probabilitythat you want to use and overwrite thedefault prediction class column Model development dataset*hr_churn_dev_data"Scoring dataset"new_data_scoring"In case you performed data prep steps on traning data, do the same steps inside thismetanodeKeep only 4 columns:- ID- pred_prob-pred_class- group_numbername the output file"scoring_group_XX", changing XX with your group numberSubstitute this nodewith the predictor of yourselected model(to be connected with the correspondinglearner)Reconfigure this nodechanging the value setting:put your group number in place of 00Rename the predictedattrition probability column "pred_prob"and the predicted class column"pred_class"Node 298 Rule Engine Excel Reader Excel Reader Data prep Column Filter Excel Writer Logistic RegressionPredictor ConstantValue Column Column Renamer Data Preparation HR ATTRITION PREDICTION Scoring new data! Develop here your main analysis (wrap the nodes into metanodes to safe space and be tidy!) Set the cut-off probabilitythat you want to use and overwrite thedefault prediction class column Model development dataset*hr_churn_dev_data"Scoring dataset"new_data_scoring"In case you performed data prep steps on traning data, do the same steps inside thismetanodeKeep only 4 columns:- ID- pred_prob-pred_class- group_numbername the output file"scoring_group_XX", changing XX with your group numberSubstitute this nodewith the predictor of yourselected model(to be connected with the correspondinglearner)Reconfigure this nodechanging the value setting:put your group number in place of 00Rename the predictedattrition probability column "pred_prob"and the predicted class column"pred_class"Node 298 Rule Engine Excel Reader Excel Reader Data prep Column Filter Excel Writer Logistic RegressionPredictor ConstantValue Column Column Renamer Data Preparation

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Created by: Daniele
Created at: 2022-02-14
On NodePit since: 2023-12-06
Last update: 2024-11-21
Created with KNIME version: v5.1.1

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