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kn_​forum_​43208_​svm_​model_​sdf

forum (43208) question about SVM model and strange results

forum (43208) question about SVM model and strange results

# Run AutoML for 60 seconds or# 300 = 5 min, 600 = 10 min, 900 = 15 min, 1800 = 30 min, 3600 = 1 hour, # 7200 = 2 hours# 14400 = 4 hours# 16200 = 4.5 hours# 18000 = 5 Stunden# 21600 = 6 hours# 25200 = 7 hours# 28800 = 8 hours# 36000 = 10 hours forum (43208) question about SVM model and strange resultshttps://forum.knime.com/t/svm-node-cant-identify-true-positives-and-false-positives/43208/11?u=mlauber71(initial workflow by: Soren_Therkel) AKR1C3.xlsxedit: v_runtime_automlset the maximum runtime ofH2O.ai AutoML in SECONDSReading in3D dataAKR1C3_3D.sdfDistribution ofclassesNode 84Node 32Node 90Node 93Node 94Node 98train.tableNode 100Node 101Node 103Node 109seed1654115542797TargetNode 112Node 113Node 114Node 115Node 116Score the test tableAUCPRor loglossNode 511train_non_normalized.tabletrain.tableChi2vtakes 44% of explaining power!Node 517Score the test tableNode 519Node 520Node 521Node 522Node 523h2o_automl_model.zipExcel Reader Integer Input Metanode 0 : 1 Bar Chart(JFreeChart) Normalizer X-Partitioner X-Aggregator SVM Learner SVM Predictor Scorer (JavaScript) Table Writer GroupBy Binary ClassificationInspector XGBoost Predictor Binary ClassificationInspector Partitioning Rule Engine Rank Correlation Random ForestLearner Random ForestPredictor Binary ClassificationInspector Scorer (JavaScript) H2O MOJO Predictor(Classification) H2O AutoML Learner H2O Local Context Table to H2O H2O Model to MOJO Binary ClassificationInspector Data preparation Table Writer Table Reader H2O Gradient BoostingMachine Learner H2O Model to MOJO Binary ClassificationInspector H2O MOJO Predictor(Classification) Scorer (JavaScript) Scorer (JavaScript) Scorer (JavaScript) Domain Calculator XGBoost LinearEnsemble Learner H2O MOJO Writer # Run AutoML for 60 seconds or# 300 = 5 min, 600 = 10 min, 900 = 15 min, 1800 = 30 min, 3600 = 1 hour, # 7200 = 2 hours# 14400 = 4 hours# 16200 = 4.5 hours# 18000 = 5 Stunden# 21600 = 6 hours# 25200 = 7 hours# 28800 = 8 hours# 36000 = 10 hours forum (43208) question about SVM model and strange resultshttps://forum.knime.com/t/svm-node-cant-identify-true-positives-and-false-positives/43208/11?u=mlauber71(initial workflow by: Soren_Therkel) AKR1C3.xlsxedit: v_runtime_automlset the maximum runtime ofH2O.ai AutoML in SECONDSReading in3D dataAKR1C3_3D.sdfDistribution ofclassesNode 84Node 32Node 90Node 93Node 94Node 98train.tableNode 100Node 101Node 103Node 109seed1654115542797TargetNode 112Node 113Node 114Node 115Node 116Score the test tableAUCPRor loglossNode 511train_non_normalized.tabletrain.tableChi2vtakes 44% of explaining power!Node 517Score the test tableNode 519Node 520Node 521Node 522Node 523h2o_automl_model.zipExcel Reader Integer Input Metanode 0 : 1 Bar Chart(JFreeChart) Normalizer X-Partitioner X-Aggregator SVM Learner SVM Predictor Scorer (JavaScript) Table Writer GroupBy Binary ClassificationInspector XGBoost Predictor Binary ClassificationInspector Partitioning Rule Engine Rank Correlation Random ForestLearner Random ForestPredictor Binary ClassificationInspector Scorer (JavaScript) H2O MOJO Predictor(Classification) H2O AutoML Learner H2O Local Context Table to H2O H2O Model to MOJO Binary ClassificationInspector Data preparation Table Writer Table Reader H2O Gradient BoostingMachine Learner H2O Model to MOJO Binary ClassificationInspector H2O MOJO Predictor(Classification) Scorer (JavaScript) Scorer (JavaScript) Scorer (JavaScript) Domain Calculator XGBoost LinearEnsemble Learner H2O MOJO Writer

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Created by: sorentherkelsen
Created at: 2022-06-01
On NodePit since: 2022-06-04
Last update: 2024-04-27
Created with KNIME version: v4.5.2
Tags: svm

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