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wine data classification - solution

Wine data classification exerciseData: 178 wines and their attributes (13 numerical features)Goal: Build a classifier for Type (1 / 2 / 3)1. Data is read from the table file2.Converting Type to string3. Partitioning to the training data (60%) and testing data (40%)4. Random forest model5. Parameter optimization6. Cross validation Random forest modelRandom Forest Learner & PredictorTree depth = 2Number of models = 20Otherwise default setting Parameter optimizationParameter Optimization Loop Start & EndTree depth: 2 to 8, step size=1Number of models: 10 to 100, step size=10Maximize accuracy Cross validationX-Partitioner & X-Aggregator5-fold cross validation, stratified sampling on TypeRandom forest model, tree depth=5, number of models=20 reading thedata tableTraining 60%Testing 40%ConvertingType tostring Table Reader Partitioning Random ForestLearner Random ForestPredictor Scorer Number To String Random ForestPredictor Scorer Random ForestLearner Parameter OptimizationLoop Start ParameterOptimization Loop End Random ForestLearner Random ForestPredictor X-Partitioner X-Aggregator Scorer Wine data classification exerciseData: 178 wines and their attributes (13 numerical features)Goal: Build a classifier for Type (1 / 2 / 3)1. Data is read from the table file2.Converting Type to string3. Partitioning to the training data (60%) and testing data (40%)4. Random forest model5. Parameter optimization6. Cross validation Random forest modelRandom Forest Learner & PredictorTree depth = 2Number of models = 20Otherwise default setting Parameter optimizationParameter Optimization Loop Start & EndTree depth: 2 to 8, step size=1Number of models: 10 to 100, step size=10Maximize accuracy Cross validationX-Partitioner & X-Aggregator5-fold cross validation, stratified sampling on TypeRandom forest model, tree depth=5, number of models=20 reading thedata tableTraining 60%Testing 40%ConvertingType tostringTable Reader Partitioning Random ForestLearner Random ForestPredictor Scorer Number To String Random ForestPredictor Scorer Random ForestLearner Parameter OptimizationLoop Start ParameterOptimization Loop End Random ForestLearner Random ForestPredictor X-Partitioner X-Aggregator Scorer

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Created by: Satoru
Created at: 2022-12-06
On NodePit since: 2023-01-25
Last update: 2024-04-28
Created with KNIME version: v4.7.0

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