Kaggle competition: Categorical Feature Encoding Challenge II
<SOS> metric: AUC Kaggle data source: categorical-feature-encoding-challenge-ii<compute_test_metric>
!wget https://download.knime.org/analytics-platform/linux/knime_4.1.2.linux.gtk.x86_64.tar.gz
!tar xvzf knime_4.1.2.linux.gtk.x86_64.tar.gz
!rm knime_4.1.2.linux.gtk.x86_64.tar.gz
!unzip./knime_4.1.2/knime-workspace.zip -d./knime_4.1.2/knime-workspace/
!rm./knime_4.1.2/knime-workspace.zip
!cp -R /kaggle/input/knime-cat-publ./knime_4.1.2/knime-workspace/
!sed -i 's/Xmx2048m/Xmx10240m/g'./knime_4.1.2/knime.ini
!./knime_4.1.2/knime -application org.eclipse.equinox.p2.director -nosplash -consolelog -r 'http://update.knime.com/analytics-platform/4.1,http://update.knime.com/community-contributions/4.1,http://update.knime.com/community-contributions/trusted/4.1,http://update.knime.com/partner/4.1' -i 'org.knime.features.python2.feature.group,org.knime.features.ext.h2o.feature.group,org.knime.features.datageneration.feature.group' -d./knime_4.1.2/
!pip install knime
!pip install dfply
print("CV score: {:<8.5f}".format(roc_auc_score(target, oof)) )<prepare_output>
knime.executable_path = "./knime_4.1.2/knime"
workspace = "./knime_4.1.2/knime-workspace"
workflow = "knime-cat-publ/cat_publ/cat_publ"
preds1 = np.array(sum(preds)/num_epochs)
 preds1<define_variables>
knime.Workflow(workflow_path=workflow,workspace_path=workspace )
all_ensemble_values = [0., 0.125, 0.25, 0.375, 0.5, 0.675, 0.75, 0.875, 1.0]<define_variables>
with knime.Workflow(workflow_path=workflow,workspace_path=workspace)as wf:
wf.execute()
<save_to_csv><EOS>