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Sampling Strategies Comparison

SamplingImbalanceSMOTE
victor_palacios profile image
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Oct 8, 2021 7:59 PM
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Experiment with: - simple random sampling - stratified random sampling (Partitioning node) - undersampling (Equal Size Sampling node) - oversampling (Bootstrap Sampling node and SMOTE node) The workflow draws on the kaggle Stroke Prediction Dataset that represents 5110 rows with 11 clinical features such as body mass index, smoking status, age, gender, and glucose level. The task is to predict stroke (yes/no), which is a classification problem. We chose to build a Random Forest model.
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Created with KNIME Analytics Platform version 4.4.2
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    KNIME Base nodesTrusted extension

    KNIME AG, Zurich, Switzerland

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    KNIME Ensemble Learning WrappersTrusted extension

    KNIME AG, Zurich, Switzerland

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    KNIME Machine Learning Interpretability ExtensionTrusted extension

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