Hi Garad,
Did you use the BenaPro Dataset provided as part of the Demo Data or did you create your own Dataset from Scratch ?
Did you use postman or the ThingWorx Analytics Builder to run the analytics jobs ?
Now as far understanding the outcome is concerned in analytics is on a case by case basis so no general interpretations could be provided for specific results. However, a broad definition of the concepts you mentioned would be :
-The Goal: A “Goal” in ThingWorx Analytics is the same as an outcome variable or “dependent variable”.
-The features or Independent Variables : is the information available to help us predict or explain an outcome whereas the dependent variable (Goal) is the outcome we are trying to predict or understand.
-The SignalsA “Signal” represents the strength or weakness a particular input (independent variable) has in relation to the Topic (dependent variable)
-Model: This is a mathematical Equation representing the relationship between the Goal and the independent Variables created through ThingWorx Analytics Machine learning algorithms. Its accuracy is measured through different methods like RMSE or Pearson correlations. The Model is trained based on the historical Data available in the Dataset you provide
To perform the scoring a new set of records in the Dataset in provided to the TWA engine in which the values of the Goal Variable are unknown. So in predictive analytics, scoring consists of trying to find the unknown values of the goal through previously trained model. This is done when running a scoring job.
Also please refer to the below videos link that could be helpful when using the TWA Builder:
https://community.thingworx.com/videos/
I hope this helps.
Best Regards,
Amine
