- 09.02.2020

Rapidminer parallel

rapidminer parallelA new parallel execution framework. With RapidMiner , we introduce a new parallel execution framework under the hood of RapidMiner Studio. Hi so I know the old parallel processing extension is no longer functional and I understand that you're working on parallelization of other.

"Parallel Processing Extension"

Share on facebook Rapidminer parallel on linkedin There have been some major advancements rapidminer parallel the RapidMiner platform since this article was originally published.

While simplifying a lot, this catchy phrase is certainly valid when summarizing the challenges for data scientists.

Rapidminer parallel

Data science is becoming the key guide showing companies where to move and how and this translates directly into the rapidminer parallel challenge for data scientists: produce as much valuable insight and knowledge in as little time as possible.

Speed is of the essence, not results alone. Time is money. Accelerating Analytics: Building it and rapidminer parallel it At RapidMiner, it is one of our key objectives to accelerate analytics and to help data scientists deliver accurate and valuable rapidminer parallel faster.

For quite some time now, we have been focusing on supporting data scientists to build analytics faster, rapidminer parallel.

Rapidminer parallel

While this provides a decent lever to accelerate analytics, it rapidminer parallel only half of the game.

The other half is execution.

Rapidminer parallel

As such, we have now broadened our focus to speed up running analytics as well: A new parallel execution framework With RapidMiner 7. This allows you to run calculations in rapidminer parallel on multiple CPU cores, making full use rapidminer parallel the available compute resources.

Rapidminer parallel

In rapidminer parallel next couple of releases, we plan to migrate many of our operators to make use of this framework, resulting in a considerable speed up through the parallelization of computations. As a first step demonstrating the rapidminer parallel, we have parallelized one of the most important operators in RapidMiner: Cross-Validation.

Parallel execution of the

Rapidminer parallel iteration of training a model, applying it and evaluating its predictive quality is called a fold.

In short: cross-validation is used all over the place when it rapidminer parallel to modeling and model optimization.

Rapidminer parallel

I have built processes in which the rapidminer parallel operator was executed hundreds of times to figure out the best model. An excursus.

Rapidminer parallel

Parallelized cross-validation Now that we have ported the cross-validation operator to rapidminer parallel use of parallel execution, all rapidminer parallel modeling processes speed up. In the best case, a speed up equal to the number rapidminer parallel folds of your cross-validation.

Elaborate Your Time Series Analysis - RapidMiner

The rapidminer parallel is learn more here significantly rapidminer parallel time is needed to run model processes.

In effect, you get results way faster than before, rapidminer parallel explore more models, variants and parameters in less time, and ultimately produce better results faster. While modeling is a big part of the work of data scientists, there is more.

Rapidminer parallel

And there rapidminer parallel much more to do to speed up other parts of the process as well. With the go here parallel execution framework we have laid the foundation to deliver more improvements to speed up the execution of core computationally-intensive tasks in RapidMiner considerably.

Stay rapidminer parallel for related improvements in the next releases.

Rapidminer parallel

Read more, we want to help you being faster when building and rapidminer parallel analytics.

What else?

Introducing RapidMiner Go

On a final note, we could not rapidminer parallel purely a performance-related improvement without continuing to think about user experience: To rapidminer parallel usage, we have consolidated three operators related to cross-validation into a single one.

Where you previously could choose from X-Validation, Batch-X-Validation or X-Prediction operators, all of their functionality rapidminer parallel covered by the single new Cross-Validation operator now making it easier to adapt to various use case requirements rapidminer parallel image below.

Just another small improvement to accelerate analytics just a little bit further.

Rapidminer parallel

Time is money, after all. To find out what else is new in RapidMiner 7.

Rapidminer parallel

Tobias loves spending time with his two young daughters. Being outsmarted by them makes him proud.

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