You may have seen that Oracle R Distribution 3.6.1 was recently released along with compatibility for Oracle Machine Learning for R (OML4R), formerly Oracle R...
You may have seen that Oracle R Distribution 3.6.1 was recently released along with compatibility for Oracle Machine Learning for R (OML4R), formerly Oracle R Enterprise, version 1.5.1. What you may not realize is that for the past year OML4R is included with your Oracle Database license, so if you have Oracle Database, you can immediately start using OML4R in your production applications. With OML4R, data scientists and other R users are able to access and manipulate...
You may have seen that Oracle R Distribution 3.6.1 was recently released along with compatibility for Oracle Machine Learning for R (OML4R), formerly Oracle R Enterprise, version 1.5.1. What you...
In my previous post To sample or not to sample, we discussed some of the issues involved in sampling data for use in machine learning. In this post, we look at...
In my previous post To sample or not to sample, we discussed some of the issues involved in sampling data for use in machine learning. In this post, we look at using Oracle R Enterprise transparency layer to perform a few types of sampling: simple random sampling, with and without replacement, and stratified sampling. When your data is too large to fit in memory, you're left with a paradox: you need to sample the data so it fits in memory, but you need to load it into memory...
In my previous post To sample or not to sample, we discussed some of the issues involved in sampling data for use in machine learning. In this post, we look at using Oracle R Enterprise transparency...
Data sets come in many shapes and sizes. Some are tall and thin, others are short and wide. Some take on the form of dense data, a.k.a., single-record case,...
Data sets come in many shapes and sizes. Some are tall and thin, others are short and wide. Some take on the form of dense data, a.k.a., single-record case, where each row represents one entity, such as a customer or vehicle. Others take on the form of sparse data, a.k.a., transactional data, where each row typically consists of an identifier, variable name, and value, and a single "case" is represented by multiple rows sharing the same identifier. R provides a variety of...
Data sets come in many shapes and sizes. Some are tall and thin, others are short and wide. Some take on the form of dense data, a.k.a., single-record case, where each row represents one entity, such...
R users have a few choices of how to connect to Oracle Database. The most commonly seen include: RODBC, RJDBC, and ROracle. However, these three packages have...
R users have a few choices of how to connect to Oracle Database. The most commonly seen include: RODBC, RJDBC, and ROracle. However, these three packages have significantly different performance and scalability characteristics, which can greatly impact your application development. In this blog, we’ll discuss these options and highlight performance benchmark results on a wide range of data sets. This performance benchmark post is an update from our 2013 blog post and uses...
R users have a few choices of how to connect to Oracle Database. The most commonly seen include: RODBC, RJDBC, and ROracle. However, these three packages have significantly different performance...
Oracle has supported the R Consortium since its inception in 2015 ( R Consortium Launched!). As a provider of multiple software tools and products that leverage...
Oracle has supported the R Consortium since its inception in 2015 ( R Consortium Launched!). As a provider of multiple software tools and products that leverage and extend R, joining the R Consortium was a natural way for Oracle to give back to the R community and contribute to the evolution of the R ecosystem. The R Consortium provides vendors a forum within which to suggest needed projects for the R community, and to raise concerns. Through the Infrastructure Steering...
Oracle has supported the R Consortium since its inception in 2015 ( R Consortium Launched!). As a provider of multiple software tools and products that leverage and extend R, joining the R...
In a variety of machine learning applications, there are often requirements for training multiple models. For example, in the internet of things (IoT) industry,...
In a variety of machine learning applications, there are often requirements for training multiple models. For example, in the internet of things (IoT) industry, a unique model needs to be built for each household with installed sensors that measure temperature, light or power consumption. Another example can be found in the online advertising industry. To serve personalized online advertisements or recommendations, a huge number of individualized models has to be built and...
In a variety of machine learning applications, there are often requirements for training multiple models. For example, in the internet of things (IoT) industry, a unique model needs to be built for...
