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  • 05_Weak_Supervision_on_the_Adult_dataset
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Weak Supervision on the Adult dataset

Weak Supervision Weakly Supervised Learning Machine Learning Gradient Boosted Trees Logistic Regression
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This workflow shows how to use the Weak Label Model Learner and Predictor nodes to aggregate sources of weak supervision such as weak models or simple rules into a single strong source that can be used to train various models. The models trained here are Gradient Boosted Trees, Logistic Regression and Deep Learning. In the final step of the workflow these models are applied to unseen data and the results are visualized with the Binary Classification Inspector that allows to compare the performance of different models in an interactive view. The data used is a preprocessed version of the Adult dataset (https://archive.ics.uci.edu/ml/datasets/Adult)

Used extensions & nodes

Created with KNIME Analytics Platform version 4.1.0
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    KNIME Core Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

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    KNIME Deep Learning - Keras Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

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    KNIME Machine Learning Interpretability Extension Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

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    KNIME Weak Supervision Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

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