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20230526 Pikairos JustKNIMEIt Season 2 Challenge 9 What Matters for Wine Quality

In this challenge, your goal is to see which features are the most important in predicting the quality of wine. After doing this analysis, you should create a visualization that shows the features' importances in order.

Challenge 09: What Matters for Wine Quality?Description: In this challenge, your goal is to see which features are the most important inpredicting the quality of wine. After doing this analysis, you should create a visualization thatshows the features' importances in order. Wine QualityDataTrain ModelTop = 90 % training setBottom = 10% test setConvert Qualityto StringApply Model toTest SetView AccuracyStatisticsExtractRulesetConcatenateData for AllOutcomes(Predicted Quality)Loop ThroughEach PredictedOutcome(Predicted Quality)Create Upper andLower Bounds ofy-axis forParallel CoordinatesPlotExtract Names ofFeatures Usedin Decision TreeRuleset and Countthe Number of TimesEach Feature WasUsedPivot Tableto Create Matrixof Features CSV Reader DecisionTree Learner Partitioning Number To String Decision TreePredictor Scorer Decision Treeto Ruleset Loop End Group Loop Start Create Custom AxisUpper and Lower Bounds Extract FeaturesFrom Rules Create Matrix ParallelCoordinates Plot Challenge 09: What Matters for Wine Quality?Description: In this challenge, your goal is to see which features are the most important inpredicting the quality of wine. After doing this analysis, you should create a visualization thatshows the features' importances in order. Wine QualityDataTrain ModelTop = 90 % training setBottom = 10% test setConvert Qualityto StringApply Model toTest SetView AccuracyStatisticsExtractRulesetConcatenateData for AllOutcomes(Predicted Quality)Loop ThroughEach PredictedOutcome(Predicted Quality)Create Upper andLower Bounds ofy-axis forParallel CoordinatesPlotExtract Names ofFeatures Usedin Decision TreeRuleset and Countthe Number of TimesEach Feature WasUsedPivot Tableto Create Matrixof FeaturesCSV Reader DecisionTree Learner Partitioning Number To String Decision TreePredictor Scorer Decision Treeto Ruleset Loop End Group Loop Start Create Custom AxisUpper and Lower Bounds Extract FeaturesFrom Rules Create Matrix ParallelCoordinates Plot

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