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Exercise2

KBL: Chapter 4 Exercise2
Workflow: Chapter 4/Exercise 2 This is an example of how to change the classification thresholds.In the previous exercise some patterns were not correctly classified. By applyinga different set of thresholds to the output probabilities, the final wine classification can be improved.The key node of this exercise is the Rule Engine at the end, defining a set of thresholds for a more exact classification. 80% vs. 20%Node 9more conservative class.if pred class > 0.7 => class 3if pred class < 0.3 => class 1otherwise class 2normalization in [0,1]wine.datafrom folder KBLdatausing knime: protocoland relative pathto local workflow folder14-10-3Node 14Class backto 1,2,3Class to IntClass to Stringclassvspredictionclass tonumber Partitioning MultiLayerPerceptronPredictor Rule Engine Normalizer File Reader RProp MLP Learner Normalizer (Apply) Denormalizer Double To Int String Manipulation Scorer (JavaScript) String To Number Workflow: Chapter 4/Exercise 2 This is an example of how to change the classification thresholds.In the previous exercise some patterns were not correctly classified. By applyinga different set of thresholds to the output probabilities, the final wine classification can be improved.The key node of this exercise is the Rule Engine at the end, defining a set of thresholds for a more exact classification. 80% vs. 20%Node 9more conservative class.if pred class > 0.7 => class 3if pred class < 0.3 => class 1otherwise class 2normalization in [0,1]wine.datafrom folder KBLdatausing knime: protocoland relative pathto local workflow folder14-10-3Node 14Class backto 1,2,3Class to IntClass to Stringclassvspredictionclass tonumberPartitioning MultiLayerPerceptronPredictor Rule Engine Normalizer File Reader RProp MLP Learner Normalizer (Apply) Denormalizer Double To Int String Manipulation Scorer (JavaScript) String To Number

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