Weight of evidence (WOE) is a powerful tool for feature representation and evaluation in data science. In a previous blog, we explained the importance and the...
Weight of evidence (WOE) is a powerful tool for feature representation and evaluation in data science. In a previous blog, we explained the importance and the application of WOE and its byproduct Information Value (IV). One important problem to apply this powerful tool is the scalability of the computation especially when the dataset grows large. In that blog, we presented a scalable approach of computing those values by leveraging the transparency layer provided in OML5R,...
Weight of evidence (WOE) is a powerful tool for feature representation and evaluation in data science. In a previous blog, we explained the importance and the application of WOE and its byproduct...
In the post Introducing OML AutoML User Interface, I discussed how OML AutoML UI simplifies the machine learning modeling process through the automated...
In the post Introducing OML AutoML User Interface, I discussed how OML AutoML UI simplifies the machine learning modeling process through the automated experiment workflow, while adding a few delighter features such as generating OML Notebooks for selected models and supporting immediate deployment to OML Services. In this post, I’ll share 4 performance tips you could use when running OML AutoML UI experiments. Know your tier When working with Oracle Machine Learning on...
In the post Introducing OML AutoML User Interface, I discussed how OML AutoML UI simplifies the machine learning modeling process through the automated experiment workflow, while adding a...
Random Forests on data and models in a blink Fast ML Algorithms and Databases that think Machine learning free for you with no strings These are a few of my...
Random Forests on data and models in a blink Fast ML Algorithms and Databases that think Machine learning free for you with no strings These are a few of my favorite (Oracle Machine Learning) things Last Updated March 12, 2021 Oracle Machine Learning on Oracle.com Twitter: https://twitter.com/CharlieDataMine OML Public Customer References OML Blogs (including links to Github, presentation and YouTubes) • Oracle Machine Learning blog main page • The Evolution...
Random Forests on data and models in a blink Fast ML Algorithms and Databases that think Machine learning free for you with no strings These are a few of my favorite (Oracle Machine Learning)...
The short answer is no, at least not entirely. There is a lot of anticipation and hype around artificial intelligence replacing workers in all sorts of roles —...
The short answer is no, at least not entirely. There is a lot of anticipation and hype around artificial intelligence replacing workers in all sorts of roles — taxi and truck drivers, paralegals, even doctors when it comes to diagnosis. While the promise is great, today’s reality is something else. That doesn’t mean, of course, we can’t make major strides in increasing data scientist productivity through automation. A significant part of the machine learning process can be...
The short answer is no, at least not entirely. There is a lot of anticipation and hype around artificial intelligence replacing workers in all sorts of roles — taxi and truck drivers, paralegals, even...
Authors: Charlie Berger and Dohoon Kim Automotive insurance fraud involves someone deceiving an insurance company about a claim involving their personal or...
Authors: Charlie Berger and Dohoon Kim Automotive insurance fraud involves someone deceiving an insurance company about a claim involving their personal or commercial motor vehicle. It can involve giving out misleading information or providing false documentation to support the claim. Nearly one of 10 Americans would commit insurance fraud if they knew they could get away with it. Nearly one of four Americans say it’s ok to defraud insurers. About one in 10 people agree...
Authors: Charlie Berger and Dohoon Kim Automotive insurance fraud involves someone deceiving an insurance company about a claim involving their personal or commercial motor vehicle. It can involve...
My previous post Generating cluster names from a document clustering model, Part 2 provided a deeper look at SQL constructs used to retrieve model details from...
My previous post Generating cluster names from a document clustering model, Part 2 provided a deeper look at SQL constructs used to retrieve model details from a k-Means model. In this post, we'll look at using the LEAD function to construct the cluster names and the cursor ClusterLeafIds definition for selecting the leaf clusters. The following SQL builds upon the id, term, and centroid_mean subquery to concatenate the top five terms for each cluster. In this example,...
My previous post Generating cluster names from a document clustering model, Part 2 provided a deeper look at SQL constructs used to retrieve model details from a k-Means model. In this post, we'll...
My previous post, Generating cluster names from a document clustering model, included a SQL script that involved advanced SQL constructs. In this post, we'll...
My previous post, Generating cluster names from a document clustering model, included a SQL script that involved advanced SQL constructs. In this post, we'll look at those constructs used to retrieve model details from a k-Means model. These model details provide the top terms for naming each cluster. Let's get started... The following SQL allows us to retrieve the text terms in each centroid in decreasing order of their centroid value, i.e., the importance of each term in...
My previous post, Generating cluster names from a document clustering model, included a SQL script that involved advanced SQL constructs. In this post, we'll look at those constructs used to retrieve...
Text mining is a hot topic, especially for document clustering. Say you have a potentially large set of documents that you'd like to sort into some number of...
Text mining is a hot topic, especially for document clustering. Say you have a potentially large set of documents that you'd like to sort into some number of related groups. Sometimes it is enough to know which documents are in the same group (or cluster) and be able to assign new documents to the existing set of groups. However, you may also want a description of the clusters to help understand what types of documents are in those clusters. Automatically generating cluster...
Text mining is a hot topic, especially for document clustering. Say you have a potentially large set of documents that you'd like to sort into some number of related groups. Sometimes it is enough...
