Learners use hyperparameters to achieve better performance on particular
datasets. When we use a machine learning package to choose the best hyperparmeters,
the relationship between changing the hyperparameter and performance might not
be obvious. ml...
Annotating sets of genomic intervals with genomic annotations such as chromHMM Genomation is an R package to summarize, annotate and visualize genomic intervals. It contains a collection of tools for visualizing and analyzing genome-wide data sets, i.e....
As we know, a customer usually goes through a path/sequence of different channels/touchpoints before a purchase in e-commerce or conversion in other areas. In Google Analytics we can find some touchpoints more likely to assist to conversion than others that more likely to be last-click touchpoint. As most of the channels are paid for (in
by Joseph Rickert New R packages keep rolling into CRAN at a prodigious rate: 184 in May, 195 in June and July looks like it will continue the trend. I spent some time sorting through them and have picked out a few that that are interesting from a data science point of view. ANLP provides functions for building text...
In the R post, we will present how to create your own color palettes and how to work with other palettes such as RColorBrewer, wesanderson and hex codes from www.colorcombos.com for exciting color palettes.
This is Part II of the “Express dplyr” posting. If you haven’t already you might want to review Part I of this topic before proceeding although if you have some knowledge of dplyr then by all means proceed. Don’t worry – there are no tests ! In this second part we will work with some
Synopsis I'm a hugh fan of the TV show Vikings. I thought it would be cool to mine the tv shows scripts to figure out which terms are the most
The post Text Mining with R on Vikings episode scripts appeared first on Networkx.
Introduction In a recent blog post, I introduced the new R package, manhattanly, which creates interactive manhattan plots using the plotly.js engine. In this post, I describe how to create interactive Q-Q plots using the manhattanly package. Q-Q plots tell us about the distributional assumptions of the observed test statistics and are common visualisation tools
This post will be about if we can show some data in other ways to try to
tell more clearly the Oh! Foo! is this rly happening? story.
Time time ago an gif appears showing the change of the global temperatures
Well, some sites like http://gizmodo.com/ made a reference to this animation
Mmmm… ok! A kind of...
In part 1, we went over how to use data visualization and data analysis prior to machine learning. For example, we discussed how to visualize the data to identify potential issues in the dataset, examine the variable distributions, etc. In this blog post, we’ll continue by building a very simple model and using data visualization