Tag: datasets

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: 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: All Oracle Press Releases. Press Release Lawrence J. Ellison Institute for Transformative Medicine of USC Explores Breakthrough Tissue "Fingerprints" Concept for Cancer Diagnostics Using Oracle Cloud Technology Tissue “fingerprinting” enables deep-learning algorithm to predict biomarkers, prognosis and theragnosis, set to improve understanding of cancer biology and accelerate clinical workflows, new research finds. Los Angeles and Redwood Shores, CA—Jul 9, 2020 The Lawrence J. Ellison Institute for Transformative Medicine of USC (“Ellison Institute”) and Oracle reveal a promising two-step technique to train a high-confidence predictive algorithm for enhanced cancer diagnostics. The study uses novel tissue “fingerprints”—discriminating microscopic hematoxylin and eosin ... Read More

Feed: R-bloggers. Author: Philipp Probst. [This article was first published on Philipp Probst, 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.Several R packages that use different methods are out there for using gradient boosting methods.The three most famous ones are currently xgboost, catboost and lightgbm.I want to compare these three to find out which is the best one in their default mode without tuning.These algorithms are not pure gradient boosting algorithms but combine it ... Read More

Feed: R-bloggers. Author: R Consortium. [This article was first published on R Consortium, 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.This useR!2020 session and video was organized by Laura Acion, Yanina Bellini Saibene, Paola Corrales, and Paloma Rojas Saunero. Leonardo Collado Torres coordinated the blog post submission.On June 19th, 2020, we filmed a video for useR!2020 showcasing the communities and organizations we are involved in that are for Latin Americans or have Latin American participants ... Read More

Feed: Planet PostgreSQL. The first step of working with any software is getting it installed. Based on your environment, this could be as easy as a one-click installer, or require a manual that's hundreds of pages long with thousands of config bits to tune. Deploying complex applications on Kubernetes and OpenShift can often fall somewhere in the middle. For example, deploying an Operator on OpenShift can be viewed as an intimidating thing, but it doesn't have to be. Here we're going to walk through the quickest and easiest possible way to get started!Below I’ll guide you through the steps for installing ... Read More

Feed: MemSQL Blog. Author: Carl Sverre. As part of the #memsql4good initiative, hosted at MemSQL.org, MemSQL is excited to contribute to the SafeGraph COVID-19 Data Consortium. The Consortium provides free access to relevant datasets to researchers, non-profits, and governments. MemSQL has created a repository to help existing customers, and those who wish to get started with MemSQL for free, to use our software in processing coronavirus-related data.  SafeGraph is a company that offers point of interest (POI), business listing, and foot traffic data. They have started the COVID-19 Data Consortium to enable access to free data for responses to the ... Read More

Feed: Neo4j Graph Database Platform. Author: David Penick. Data is both our most valuable asset and our biggest ongoing challenge. As data grows in volume, variety and complexity, across applications, clouds and siloed systems, traditional ways of working with data no longer work. Increasingly, businesses are recognizing a need to harness all of their data, particularly their data around customers, products, partners and more – often called master data. Pressing business priorities such as compliance and digital transformation require a holistic view of this master data.Achieving that holistic view requires connecting data across a myriad of sources and silos. Connecting ... Read More

Feed: Teradata Blog. Over the past few years, the adoption of cloud object store services like AWS-S3 and Azure Blob has exploded largely because these services are simple to use, low maintenance, cost effective, and scale easily. If you are like most Teradata customers, you’ve also been experimenting with cloud object stores to determine how they can best fit into your enterprise IT ecosystem and support your business. Indeed, you may have even gone so far as to develop an entire corporate data lake strategy based on cloud object stores.Wherever you are on the cloud object store adoption curve, I’m ... Read More

Feed: Featured Blog Posts - AnalyticBridge. Author: Elise Devaux. In a general sense, synthetic data is information that is artificially generated, as opposed to collected from the real-world. But it’s important to note that synthetic data is used for a variety of purposes. As a result, there are several types of synthetic data with different properties depending on the use-cases. For instance, one scenario in which companies use synthetic data is the training of AI/ML models. Real-world data is sometimes expensive to collect, or simply hard to come by. If you take for instance self-driving vehicles, the development of software for autonomous ... Read More