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Advanced Data Mining

Advanced Data Mining - Solution

Solution to the exercise 10 for KNIME User Training
- Training a Random Forest model to predict a nominal target column
- Evaluating the performance of a classification model
- Optimizing parameters of the Random Forest model
- Performing the classification multiple times in a cross validation loop

Define ParametersCollect AccuracyCollect optimumnr of modelsWrite modelTable Reader(deprecated) X-Partitioner Partitioning MISSING ParameterOptimization Loop Start MISSING ParameterOptimization Loop End X-Aggregator Partitioning Random ForestLearner Random ForestPredictor Random ForestLearner Random ForestPredictor Random ForestLearner Random ForestPredictor Scorer Scorer Table Rowto Variable Random ForestLearner Model Writer Partitioning Random ForestLearner Random ForestPredictor MISSING BinaryClassification Inspector Column Appender DecisionTree Learner Decision TreePredictor Table Reader(deprecated) Define ParametersCollect AccuracyCollect optimumnr of modelsWrite modelTable Reader(deprecated) X-Partitioner Partitioning MISSING ParameterOptimization Loop Start MISSING ParameterOptimization Loop End X-Aggregator Partitioning Random ForestLearner Random ForestPredictor Random ForestLearner Random ForestPredictor Random ForestLearner Random ForestPredictor Scorer Scorer Table Rowto Variable Random ForestLearner Model Writer Partitioning Random ForestLearner Random ForestPredictor MISSING BinaryClassification Inspector Column Appender DecisionTree Learner Decision TreePredictor Table Reader(deprecated)

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