Time history learn/predict G3 Workflow

Time history learn/predict G3 Workflow is now available in the workflows library.

^{Time history learn/predict G3 Workflow}

Time history workflows has 4 major components

1. data engineering
2. clustering
3. feature importance
4. learning and prediction

The modifications or selection of the inputs are done in Start worker.

In the Start worker, we can specify the type for the Target Curve required in the output.

1. Points
2. Curve
3. Matrix columns

^{Type for the Target Curve}

After the execution of the Workflow, we see report worker at end of each component to view the results.

Here are some examples of the Results in Reporter worker.

^Output

^Output

^Output

In Learning and prediction , we have opportunity to explore the ML model.

Here are some Example predictions from the ML models created from executing the Workflow.

^Prediction

^Prediction

Matrix columns option is available in settings which can be used as columns when curve is changed to Heatmap chart.

^{Matrix columns}