What do you think about Inora, a company that advertises itself as the New Linear Regression Approach - Scalable to Big Data. Our data scientist also developed automated regression for big data, offering source code, even an Excel implementation, and comparing his results with traditional regression techniques. Click here for details.
This type of product raises another issue: is linear regression a technique worth using on very large data sets? This article disagrees on this. This one also cites concerns about regression in general.
Having said that, I would love to hear a different opinion. What other companies offer reliable, totally automated regression? How do they compare to Inora? At least Inora offers free source code, but limited to 1,000 observations They seem to think that more than 1,000 observations qualifies as big data, and thus should be charged a license fee. Here are some of their selling points:
DSC Resources
Additional Reading
Follow us on Twitter: @DataScienceCtrl | @AnalyticBridge
Comment
Inora is not claiming that the free version of the RAE Linear Regression software can solve complex data challenges.
The linear regression is just an application of the generalized core Math Engine to that specific task (y=mx+b). Of course, the free version is limited to a 2-class task (finding what is line and what is not line).
The Inora Math Engine is also capable of detecting and analyzing multiple patterns in any size data set. So, even though the free linear regression software is limited, it will demonstrate how the Math Engine core is different from traditional statistics, random sample and Least Squares approaches. It is the first tool of its kind to provide a purely numerical combinatory procedure which determines the mechanical components in data autonomously; hence it is the first Hyper-Mechanics data analysis tool available.
The Math Engine at the core provides the all decisive mechanical components for the automatic decision making process to reveal hidden or latent constraints, noise, outliers - simply all Unexpected Deviations (CD) in general! Based on those result parameters any functional model analysis becomes truly deterministic and true knowledge finding. Especially when it comes to Big Complex Data!
Linear Regression is by no means the solution to complex data, but the core Math Engine is the ultimate solution to big, complex data.
© 2021 TechTarget, Inc.
Powered by
Badges | Report an Issue | Privacy Policy | Terms of Service
Most Popular Content on DSC
To not miss this type of content in the future, subscribe to our newsletter.
Other popular resources
Archives: 2008-2014 | 2015-2016 | 2017-2019 | Book 1 | Book 2 | More
Most popular articles
You need to be a member of Data Science Central to add comments!
Join Data Science Central