Loading...
You are here:  Home  >  Education Resources For Use & Management of Data  >  Data Daily | Data News  >  Current Article

RapidMiner Reinvents Automated Machine Learning to Accelerate Data Science

By   /  February 12, 2018  /  No Comments

by Angela Guess

According to a recent press release, “RapidMiner™, the company that delivers real data science, fast and simple, today announced the immediate availability of RapidMiner 8.1 and RapidMiner Auto Model, a new addition to RapidMiner Studio that accelerates everything data scientists do when building machine learning models. ‘Automated machine learning promised data scientists a better, faster way to build models, but the reality never matched the hype,’ said Dr. Ingo Mierswa, founder and president of RapidMiner. ‘Today that changes with the release of RapidMiner Auto Model. When I looked closely at automated machine learning solutions, I found them to be black boxes. They restricted my ability as a data scientist to understand how the models worked and tune them when necessary. That’s reckless and sometimes, even dangerous. We built Auto Model on top of RapidMiner Studio to improve the productivity of data scientists without hiding the ability to understand how and why a model works. As data scientists need to tune or tweak models, they have the full power of the RapidMiner Studio visual workflow designer at their disposal’.”

The release goes on, “RapidMiner Auto Model accelerates the entire data science lifecycle using automated machine learning. It speeds data prep by analyzing data to identify common quality problems. It automates predictive modeling by suggesting the best machine learning techniques and then generating optimized, cross-validated predictive models. Auto Model highlights which features have the greatest impact on the desired business objective, highlighting the most important influence factors and correlations. Built in visualizations and an interactive model simulator let data scientists quickly explore the model to see how it performs under a variety of conditions.”

Read more at PR Newswire.

Photo credit: RapidMiner

You might also like...

Data Governance in Data Warehousing and BI vs. Data Governance in Big Data Analytics

Read More →