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Hyperparameters Optimization and Training a Random Forest

This workflow optimizes the hyperparameters of a random forest of decision trees and training it with the optimized hyperparameters.

Adult.csv dataset describes US census information. Output class is sex.

70% trainign 30% testNode 3Turns "?" to num value so it can be detected as missing valConfusion MatrixNode 117Node 118find mean of missing of int or doublefilter all columns except IdConfusion MatrixNode 124Node 125Node 126Nominal(Class)Node 134Group By ClassGreen(2) Red(4)Node 139Removes duplicatesNode 141Node 146Green(2) Red(4)Node 148Node 149Node 151Node 152Partitioning GroupBy String To Number Random ForestLearner Random ForestPredictor Scorer File Reader Rule Engine Missing Value Column Filter Scorer DecisionTree Learner Decision TreePredictor Linear Correlation Equal Size Sampling ParallelCoordinates Plot GroupBy Color Manager 2D/3D Scatterplot DuplicateRow Filter RowID PCA Color Manager Scorer (JavaScript) Scorer (JavaScript) Parameter OptimizationLoop Start ParameterOptimization Loop End 70% trainign 30% testNode 3Turns "?" to num value so it can be detected as missing valConfusion MatrixNode 117Node 118find mean of missing of int or doublefilter all columns except IdConfusion MatrixNode 124Node 125Node 126Nominal(Class)Node 134Group By ClassGreen(2) Red(4)Node 139Removes duplicatesNode 141Node 146Green(2) Red(4)Node 148Node 149Node 151Node 152Partitioning GroupBy String To Number Random ForestLearner Random ForestPredictor Scorer File Reader Rule Engine Missing Value Column Filter Scorer DecisionTree Learner Decision TreePredictor Linear Correlation Equal Size Sampling ParallelCoordinates Plot GroupBy Color Manager 2D/3D Scatterplot DuplicateRow Filter RowID PCA Color Manager Scorer (JavaScript) Scorer (JavaScript) Parameter OptimizationLoop Start ParameterOptimization Loop End

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