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05_​H2O_​Scoring

Workflow

H2O scoring model performance metrics
This example shows how to evaluate the performance of H2O classification (binominal and multinominal) and regression models.
H2O scoring machine learning model evaluation
Scoring with H2O In this example we take a look at the KNIME Nodes for H2O Scoring.There are different H2O Scorer Nodes in KNIME for different Machine Learning problems: The "H2O Regression Scorer" Node for regression problems and the Classification Scorer Nodes for Binominaland Multinominal classifiers. Depending on the problem (the type of the response) different scoring metrics arecomputed. 1. Classification scoring:In order to Score binominal or multinominal classifiers, we have to add columns with the per-class probabilities.This can be achieved by activating the setting "append individual class probabliities" in the H2O PredictorNodes.The "H2O Binominal Scorer" Node computes classification metrics for response variables with two classes,resulting in Accuracy Statistics (Output Port 0), the confusion matrix (Output Port 1) and the gains lift (OutputPort 2).The H2O Multinominal Scorer Node computes classification metrics (Output Port 0) for multilabel responsevariables (3 or more classes) as well as the confusion matrix (Output Port 1).2. Regression scoring:The H2O Regression Scorer Node computes regression metrics like the RSME and R-Squared (Output Port 0). H2O scoring example 1. Classification scoring 2. Regression scoring Start local H2O Single Node instanceRegression metricsDo predictionDo prediction & append class probabilitiesDo prediction & append class probabilitiesBinominal metricsMultinominal classification metrics and Confusion Matrix H2O Local Context H2O Numeric Scorer H2O Predictor(Regression) Load carspeed dataand learn model Load IRIS dataand learn model Load binominal dataand learn model H2O Predictor(Classification) H2O Predictor(Classification) H2O Binomial Scorer H2O MultinomialScorer Scoring with H2O In this example we take a look at the KNIME Nodes for H2O Scoring.There are different H2O Scorer Nodes in KNIME for different Machine Learning problems: The "H2O Regression Scorer" Node for regression problems and the Classification Scorer Nodes for Binominaland Multinominal classifiers. Depending on the problem (the type of the response) different scoring metrics arecomputed. 1. Classification scoring:In order to Score binominal or multinominal classifiers, we have to add columns with the per-class probabilities.This can be achieved by activating the setting "append individual class probabliities" in the H2O PredictorNodes.The "H2O Binominal Scorer" Node computes classification metrics for response variables with two classes,resulting in Accuracy Statistics (Output Port 0), the confusion matrix (Output Port 1) and the gains lift (OutputPort 2).The H2O Multinominal Scorer Node computes classification metrics (Output Port 0) for multilabel responsevariables (3 or more classes) as well as the confusion matrix (Output Port 1).2. Regression scoring:The H2O Regression Scorer Node computes regression metrics like the RSME and R-Squared (Output Port 0). H2O scoring example 1. Classification scoring 2. Regression scoring Start local H2O Single Node instanceRegression metricsDo predictionDo prediction & append class probabilitiesDo prediction & append class probabilitiesBinominal metricsMultinominal classification metrics and Confusion Matrix H2O Local Context H2O Numeric Scorer H2O Predictor(Regression) Load carspeed dataand learn model Load IRIS dataand learn model Load binominal dataand learn model H2O Predictor(Classification) H2O Predictor(Classification) H2O Binomial Scorer H2O MultinomialScorer

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Nodes

05_​H2O_​Scoring consists of the following 19 nodes(s):

Plugins

05_​H2O_​Scoring contains nodes provided by the following 3 plugin(s):