The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Contrast trees are used to assess the accuracy of many types of machine learning estimates that are not amenable to standard validation techniques. These include properties of the conditional distribution \(p_{y}(y\,|\,\mathbf{x})\) (means, quantiles, complete distribution) as functions of \(\mathbf{x}\). Given a set of predictor variables \(\mathbf{x}=(x_{1},x_{2},\)\(,x_{p})\) and two outcome variables \(y\) and \(z\) associated with each \(\mathbf{x}\), a contrast tree attempts to partition the space of \(\mathbf{x}\) values into local regions within which the respective distributions of \(y\,|\,\mathbf{x}\) and \(z\,|\,\mathbf{x}\), or selected properties of those distributions such as means or quantiles, are most different.
For more details, please see the tutorial.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.