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28 feb. 2017

Machine Learning: Choosing the right estimator



Often the hardest part of solving a machine learning problem can be finding the right estimator for the job.
Different estimators are better suited for different types of data and different problems.


The flowchart below by Scikit Learn is designed to give users a bit of a rough guide on how to approach problems with regard to which estimators to try on your data

24 feb. 2017

Leaflet and R


Leaflet 1.1.0 is now available on CRAN! The Leaflet package is a tidy wrapper for the Leaflet.js mapping library, and makes it incredibly easy to generate interactive maps based on spatial data you have in R.




Leaflet is one of the most popular open-source JavaScript libraries for interactive maps. It’s used by websites ranging from The New York Times and The Washington Post to GitHub and Flickr, as well as GIS specialists like OpenStreetMap, Mapbox, and CartoDB

This release was nearly a year in the making, and includes many important new features.
  • Easily add textual labels on markers, polygons, etc., either on hover or statically
  • Highlight polygons, lines, circles, and rectangles on hover
  • Markers can now be configured with a variety of colors and icons, via integration with Leaflet.awesome-markers
  • Built-in support for many types of objects from sf, a new way of representing spatial data in R (all basic sf/sfc/sfg types except MULTIPOINT and GEOMETRYCOLLECTION are directly supported)
  • Projections other than Web Mercator are now supported via Proj4Leaflet
  • Color palette functions now natively support viridis palettes; use "viridis", "magma", "inferno", or "plasma" as the palette argument
  • Discrete color palette functions (colorBin, colorQuantile, and colorFactor) work much better with color brewer palettes
  • Integration with several Leaflet.js utility plugins
  • Data with NA points or zero rows no longer causes errors
  • Support for linked brushing and filtering, via Crosstalk (more about this to come in another blog post)
Visto en blog.rstudio

23 feb. 2017

Citus 6.1 Released, escala tu Base de datos PostgreSQL


Interesantes novedades de Citusdata, ver Community Edition

Citus es una base de datos distribuida que permite escalar PostgreSQL (una de nuestras Bases de Datos favoritas), permitiendo usar todas las funcionalidades de PostgreSQL con las ventajas de escalar.

Microservices and NoSQL get a lot of hype, but in many cases what you really want is a relational database that simply works, and can easily scale as your application data grows. Microservices can help you split up areas of concern, but also introduce complexity and often heavy engineering work to migrate to them. Yet, there are a lot of monolithic apps out that do need to scale. 

If you don’t want the added complexity of microservices, but do need to continue scaling your relational database then you can with Citus. With Citus 6.1 we’re continuing to make scaling out your database even easier with all the benefits of Postgres (SQL, JSONB, PostGIS, indexes, etc.) still packed in there.

With this new release customers like Heap and Convertflow are able to scale from single node Postgres to horizontal linear scale. Citus 6.1 brings several improvements, making scaling your multi-tenant app even easier. These include:
  • Integrated reference table support
  • Tenant Isolation
  • View support on distributed tables
  • Distributed Vaccum / Analyze

All of this with the same language bindings, clients, drivers, libraries (like ActiveRecord) that Postgres already works with