var modelFeatures = Resources["InfoTableFunctions"].CreateInfoTable({infoTableName: "modelFeatures"});
modelFeatures.AddField({name: "name", baseType: "STRING"});
modelFeatures.AddField({name: "description", baseType: "STRING"});
modelFeatures.AddRow({name: "AmbientTemperature"});
modelFeatures.AddRow({name: "ExhaustVacuum"});
modelFeatures.AddRow({name: "AmbientPressure"});
modelFeatures.AddRow({name: "RelativeHumidity"});
modelFeatures.AddRow({name: "ElectricalOutput"});

var learners = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape( {infoTableName : "learners", dataShapeName : "AnalyticsTrainingLearner"});
learners.AddRow({learningTechnique: "NEURAL_NET"});

var metadata = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape({infoTableName : "InfoTable",dataShapeName : "AnalyticsDatasetMetadataFlattened"});
for(var i=0; i<modelFeatures.rows.length; i++){
   metadata.AddRow({fieldName: modelFeatures.rows[i].name, dataType: "DOUBLE", opType: "CONTINUOUS" });
}

var data =  me.QueryNamedPropertyHistory({
   propertyNames: modelFeatures,
   maxItems: 10000
});
data.RemoveField("timestamp");

var datasetref = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape({ dataShapeName: "AnalyticsDatasetRef" });
datasetref.AddRow({data: data, metadata: metadata});

me.ModelResultID =  Things["AnalyticsServer_TrainingThing"].CreateJob({
                jobName: "Test_Training" /* STRING */,
                learners: learners /* INFOTABLE */,
                goalField: me.Goal /* STRING */,
                datasetRef: datasetref /* INFOTABLE */,
});