Building an Interactive Globe Visualization in R
In this earlier post we analysed the location of meteorite impacts from this dataset, including plotting their fall locations on a globe. Forming part of...
[Read more...]
Articles by Jake Hoare
How to Aggregate Data in R
The process involves two stages. First, collate individual cases of raw data together with a grouping variable. Second, perform which calculation you want on each... [Read more...]
Predict Customer Churn with Gradient Boosting
Customer churn is a key predictor of the long term success or failure of a business. But when it comes to all this data, what’s...
How to Format Numbers, Dates, and Time Using in D3 HTMLWidgets in R
If you have ever spent any time investigating where the cool kids play in the data visualization world you will know it is all about... [Read more...]
How to Build a Geographic Dashboard with Real-Time Data
In this post, I show how to build an interactive geographic dashboard using Displayr, Plotly and R. It is particularly fascinating in that it tracks...
Linear Discriminant Analysis in R: An Introduction
How does Linear Discriminant Analysis work and how do you use it in R? This post answers these questions and provides an introduction to Linear... [Read more...]
Goodness of Fit in MDS and t-SNE with Shepard Diagrams
The goodness of fit for data reduction techniques such as MDS and t-SNE can be easily assessed with Shepard diagrams. A Shepard diagram compares how far apart your data points are before and after you transform... [Read more...]
Analyzing Google Trends Data in R
Google Trends shows the changes in the popularity of search terms over a given time (i.e., number of hits over time). It can be used to find search terms with growing or decreasing popularity or to review periodic variations from the past such as seasonality. Google Trends search data ...
Analyzing Google Trends Data in R
Google Trends shows the changes in the popularity of search terms over a given time (i.e., number of hits over time). It can be used to find search terms with growing or decreasing popularity or... [Read more...]
Automatically Fitting the Support Vector Machine Cost Parameter
In an earlier post I discussed how to avoid overfitting when using Support Vector Machines. This was achieved using cross validation. In cross validation, prediction accuracy is maximized by varying the cost parameter. Importantly, prediction accuracy is... [Read more...]
Using Partial Least Squares to Conduct Relative Importance analysis in R
Partial Least Squares (PLS) is a popular method for relative importance analysis in fields where the data typically includes more predictors than observations. Relative importance analysis is a general term applied to any technique used for...
Using Partial Least Squares to conduct relative importance analysis in Displayr
Partial Least Squares (PLS) is a popular method for relative importance analysis in fields where the data typically includes more predictors than observations. Relative importance analysis is a general term applied to any technique used for... [Read more...]
Gradient Boosting – the coolest kid on the machine learning block
Gradient boosting is a technique attracting attention for its prediction speed and accuracy, especially with large and complex data. Don’t just take my word for it, the chart below shows the rapid growth of Google...
Copyright © 2022 | MH Corporate basic by MH Themes