












Redial Basis Functions
are a large class of approximating functions, computed as a
linear combination of nonlinear functions of the distances
to a set of centres:









Rank (of a matrix)
The number of linearly independent rows columns.









Regularization
A class of methods of avoiding overfitting to the training
set by penalizing the fit by a measure of 'smoothness' of the
fitted function.









Resistant Methods
are designed to be little affected by outliers. For example,
the median is much resistant than the mean.









R Factor Analysis
Analyzes relationships among variables to identify groups of
variables forming latent dimension (factors).









Reliability
Extent to which a variables or set of variables is consistent
in what it is intended to measure. If multiple measurements
are taken, reliable measures will all be very consistent in
their values. If differs from validity in that it does not relate
to what should be measured, but instead to how it is measured.









Reverse Scoring
Process of reversing the scores of a variable, which retaining
the distributional characteristics, to change the relationships
(correlations) between two variables. Used in summated scale
construction to avoid a ¡°canceling out¡± between variables with
positive and negative factor loadings on the same factor.









Ridge Regression
See shrinkage methods.









Risk
of a classifier is the expected loss from using it. The bayes
risk is the lowest attainable risk (using these features).









Robust Methods
are designed to be resistant, and also to have high efficiency
near some target distribution. For example, although the median
is resistant, it is inefficient compared to a trimmed mean.









