nav[aria-label="Primary Navigation"] { padding: 0; & ul { list-style: none; width: 100%; display: flex; flex-direction: row; justify-content: start; align-items: start; gap: 30px; padding: 0; & li { margin: 0; } & ul li { list-style: none; } } }

Siemens Community Catalyst Program

The Siemens Community Catalyst program was co-created with our community to acknowledge technology leaders who consistently contribute to the Siemens Community. Nominations are accepted on a rolling basis.

Nominate Now

Cross Validation

islem_h

Hi everyone,

I am using different regression models to predict electricity consumption. To evaluate my models I use cross validation so I have process and subprocess. How can I see the predictions my models make? I mean where should I place the "Explain Prediction" operator?
and For Randm Forest, where should I place the " Weights by Tree Importance" operator to have an idea about the prediction power of the attributes.

This would be very helpful, thank you in advance!

Find more posts tagged with

AI Studio

Cross Validation

Accepted answers

Telcontar120

In both cases, you should put the operators outside the Cross Validation. If you want to see the predictions on your full dataset, you should connect the "Test" ouput port from the right-hand side of the inner cross-validation, and then pull that through on the outside. That will give you your fully scored exampleset (and you will be able to use the operators you mention above).

All comments

nicholaswongsg

Hey Islem_h! Your project really sound exciting. Cross validation operator is a really powerful tool! It can be used to estimate the statistical performance of a learning model. Below I have set up a project with cross validation in place which you can take a look at it.

I have uploaded the image to my drive because I'm facing an error while uploading it here. Probably because I just joined. drive(dot)google(dot)com/open?id=1B11WunE16eQxLWD_6CAbqG_9F1jE0I0w

Hope this help with what you want to achieve.

sgenzer

@nicholaswongsg I just gave you a Boost badge - you should move up from Newbie and be able to post links now

islem_h

Hi @nicholaswongsg ,
the project you shared shows only a simple example of where to place the cross validation operator.
My question was rather, in the case I am using cross validation which means I have a process and a subprocess: How can I see the predictions my models make? I mean where should I place the "Explain Prediction" operator?
and For Randm Forest, where should I place the " Weights by Tree Importance" operator to have an idea about the prediction power of the attributes.

Telcontar120

islem_h

Thank you @Telcontar120 for you answer!

Quick Links

Upcoming Events

Advancing power electronics design with Simcenter PSIM and High-Performance Computing
Join us for a community conversation on how High-Performance Computing (HPC) and Simcenter PSIM work together to meet the increasing demands of modern power electronics simulation. During this one-hour technical session, you'll discover how leveraging HPC can speed up simulations, improve scalability, and empower engineers…
Getting Started with Faster Motor Building in Simcenter Simlab
Join us for a community conversation on accelerating your motor simulation workflow with Simcenter Simlab. In this beginner-friendly session, we'll introduce the platform's automated model-building capabilities and show how easy it is to set up your first electric motor analysis. You'll see the basic steps of geometry…
Practical hybrid solver workflows in Simcenter Feko
Join us for a Community Conversation where we'll discuss practical approaches to analyzing complex electromagnetic models using hybrid solver techniques. This session will provide a general overview of how different computational methods can be combined within a single simulation to address models containing varied…

View all community events