Tag: value

Feed: R-bloggers. Author: Daniel Petzold. [This article was first published on RStudio Blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.Photo by Daniel Jerez on UnsplashData science can feel like an endless tunnel, with tremendous investment at the beginning and little visibility into where or when your results will emerge. Data science teams wrestle with many challenges, such as rapid iteration of new ideas, business alignment, productivity, transparency, and delivering durable value.As we’ve discussed ... Read More

Feed: R-bloggers. Author: Bluecology blog. [This article was first published on Bluecology blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.When we perform a statistical test we’d like to have confidence what theType I error rate is what we say it is (rate of false positivefindings). Often scientists choose a rate (AKA ‘alpha’) of 0.05 forrejecting the null hypothesis.We’d like some guarantees that our statistical test will actually have atype I rate of 5% ... Read More

Feed: R-bloggers. Author: Artful Analytics. [This article was first published on Artful Analytics, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.How I deal with wide datasets when building a predictive modelIntroductionIn this post, I will describe a preprocessing workflow that I usewhenever I have a lot variables (wide data) and need to build apredictive model quickly.The workflow has three stages:Univariate feature selection using the{Information}packageFeature engineering using the{vtreat}packageRemoval of redundant features using the{caret}packageThe overall goal ... Read More

Feed: IBM Big Data & Analytics Hub - All Content; Author: jennifer-clemente; Follow @IBMDataIn the airline industry, timing and synchronization are everything when it comes to the customer experience. Mitigating unforeseen circumstances against customer expectations and good old supply and demand are all issues well within the wheelhouse of AI’s predictive capabilities. It’s no wonder that Deutsche Lufthansa AG, Germany’s largest airline, recognized early on that with the right data and AI strategy, it could enhance the customer experience and better empower its employees while achieving operational excellence. In less than two years, the airline has quickly moved from AI ... Read More

Feed: AWS Architecture Blog. We recently published a significant update to the AWS Well-Architected Framework, and as part of that update, the Performance Efficiency Pillar whitepaper has been streamlined and improved. The questions in the whitepaper are now better aligned with those in the AWS Well-Architected Tool, making it easy to cross-reference between them when reviewing workloads. With clearer headings and each best practice highlighted, you can quickly find what you need and then dive deep on any topic.We also updated the Performance Efficiency pillar to reflect the evolution of AWS and the best practices we are seeing in the ... Read More

Feed: Recent Announcements. Starting today, you can assign tags to dataset groups, datasets, dataset import jobs, predictors, forecasts and forecast export jobs within Forecast. Each tag is a simple label consisting of a customer-defined key and an optional value that can make it easier to manage and filter resources. Tagging allows you to better manage and classify your Forecast resources and enables several use cases including providing access control and security risk management to name a few. Without tags, enterprises or independent software vendors (ISVs) with multiple resources and users would need to define an Amazon Resource Name (ARN) for ... Read More

Feed: Recent Announcements. When using the XFF header in an IP match rule, you can block requests to your application based either on the client’s original IP or on a proxy’s IP by specifying the position of the IP address. For example, to block based on client’s original IP, you can set the position to first IP found within the header value to block on client’s original IP, or set to last or any IP found to block on proxy’s IP. When using the XFF header on rate-based rules for rate limiting, or on geographic match rules for geofencing based ... Read More

Feed: The Internet of Things on AWS – Official Blog. Author: Amanda Lowe. Manufacturing industries only realize 20 to 30 percent of the value of their data. By consistently leveraging the value of their data, manufacturing companies could reduce product development costs by up to 50 percent and operating costs by up to 25 percent, while increasing their gross margins by one third[1]. Industrial IoT (IIoT) is a data lever – it brings machines, field assets at the edge, cloud computing, analytics, and people together to improve the performance and productivity of industrial processes. With IIoT, industrial companies can digitize ... Read More

Feed: Actian. Author: Sampa Choudhuri. ETL (extract, transfer, and load) and IPaaS (Integration Platform as a Service) are data integration methods to connect different IT systems and data sources together. While ETL is a set of techniques for moving data, IPaaS is a more holistic set of capabilities for moving and integrating data between IT systems.  IPaaS is often seen as the successor or “next-generation” of ETL tools – optimized to operate in modern cloud IT environments.The digital transformation of business has brought about rapid growth in the number of diverse IT systems a company uses to support its business ... Read More

Feed: Planet MySQL; Author: MySQL Performance Blog; You got yourself a Kubernetes cluster and are now testing our Percona Kubernetes Operator for Percona XtraDB Cluster. Everything is working great and you decided that you want to increase the number of Percona XtraDB Cluster (PXC) pods from the default 3, to let’s say, 5 pods. It’s just a matter of running the following command: kubectl patch pxc cluster1 --type='json' -p='[{"op": "replace", "path": "/spec/pxc/size", "value": 5 }]'kubectl patch pxc cluster1 --type='json' -p='[{"op": "replace", "path": "/spec/pxc/size", "value": 5 }]'Good, you run the command without issues and now you will have 5 pxc pods! ... Read More