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E - Commerce Customer Churn

(Output Node)Here, you can either expand this component & connectto output node & the rest of the workflow or choose thebest model & connect it separately to the workflow E Commerce Customer Churn Prediction Importing Data, EDA & Data Preprocessing Feature Engineering, Balancing Target Variables Choosing Best Model (84% Acc), Prediction Output, Exporting Data DATA Export Transform Load Feature Engineering Machine Learning Modelling Using Python Scripts Prediction Output Demo on how to usePython in KNIME:>>Data is Split in Python *Data_Num - Int & Float *Data_Cat - Object>>Data is then appended>>Visualize a scatter plot Reading Data, EDA using Python in KNIME Plotting the Data using Python in KNIME Churn PredictionInitial DataZ - Score NormalizationAfter NormalizationOutlier after NormalizationCorrelation CheckCorrelation CheckTrain & TestAfter EncodingPartition TrainPartition TestTreating Imbalanced DataData After SMOTEFinal OutputSelect Columns for Test DataChurn Prediction DBData_NumOnly Int & FloatTreat Pandas NaN to KNIME '?'Data_CatOnly ObjectsAppended DataAppending BothSelect Columns Excel Reader Data Explorer Normalizer Data Explorer Box Plot Scatter Plot(JFreeChart) Linear Correlation Partitioning Data Explorer Data Explorer Data Explorer SMOTE Data Explorer CSV Writer Column Filter MySQL Connector DB SQL Executor DB Query Reader Python Script Image to Report Python View Data Explorer Math Formula(Multi Column) Python Script Data Explorer Data Explorer Column Appender Column Filter Data Analysis Data Analysis -After Modelling One Hot Encoding Data Preprocessing Modelling (Output Node)Here, you can either expand this component & connectto output node & the rest of the workflow or choose thebest model & connect it separately to the workflow E Commerce Customer Churn Prediction Importing Data, EDA & Data Preprocessing Feature Engineering, Balancing Target Variables Choosing Best Model (84% Acc), Prediction Output, Exporting Data DATA Export Transform Load Feature Engineering Machine Learning Modelling Using Python Scripts Prediction Output Demo on how to usePython in KNIME:>>Data is Split in Python *Data_Num - Int & Float *Data_Cat - Object>>Data is then appended>>Visualize a scatter plot Reading Data, EDA using Python in KNIME Plotting the Data using Python in KNIME Churn PredictionInitial DataZ - Score NormalizationAfter NormalizationOutlier after NormalizationCorrelation CheckCorrelation CheckTrain & TestAfter EncodingPartition TrainPartition TestTreating Imbalanced DataData After SMOTEFinal OutputSelect Columns for Test DataChurn Prediction DBData_NumOnly Int & FloatTreat Pandas NaN to KNIME '?'Data_CatOnly ObjectsAppended DataAppending BothSelect Columns Excel Reader Data Explorer Normalizer Data Explorer Box Plot Scatter Plot(JFreeChart) Linear Correlation Partitioning Data Explorer Data Explorer Data Explorer SMOTE Data Explorer CSV Writer Column Filter MySQL Connector DB SQL Executor DB Query Reader Python Script Image to Report Python View Data Explorer Math Formula(Multi Column) Python Script Data Explorer Data Explorer Column Appender Column Filter Data Analysis Data Analysis -After Modelling One Hot Encoding Data Preprocessing Modelling

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: augus
Created at: 2021-11-14
On NodePit since: 2021-12-29
Last update: 2024-04-17
Created with KNIME version: v4.5.0

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