summarization {ECoL} | R Documentation |
Post-processing alternatives to deal with multiples values. This method is used by the complexity measures to summarize the obtained values.
summarization(measure, summary = c("mean", "sd"), multiple = TRUE, ...)
measure |
A list with the complexity measures values. |
summary |
The functions to post processing the data. See the details
to more information. Default: |
multiple |
A logical value defining if the measure should return
multiple values. (Default: |
... |
Extra values used to the functions of summarization. |
The post processing functions are used to summarize the complexity measures. They are organized into three groups: return, descriptive statistic and distribution. Currently, the hypothesis testing post processing are not supported.
In practice, there are no difference among the types, so that more than one
type and functions can be combined. Usually, these function are used to
summarize a set of values for each complexity measures. For instance, a
measure computed for each attribute can be summarized using the
"mean"
and/or "sd"
.
In addition to the native functions available in R, the following functions can be used:
Computes a histogram of the given data value. The extra
parameters 'bins
' can be used to define the number of values to
be returned. The parameters 'max
' and 'min
' are used to
define the range of the data. The default value for these parameters
are respectively 10, min(x)
and max(x)
.
See kurtosis
See max
See mean
See median
See min
See quantile
See sd
See skewness
See var
Returns the original value(s) of the complexity measure.
These functions are not restrictive, thus another functions can be applied as post-processing summarization function.
A list with the post-processed complexity measures.
Albert Orriols-Puig, Nuria Macia and Tin K Ho. (2010). Documentation for the data complexity library in C++. Technical Report. La Salle - Universitat Ramon Llull.
summarization(runif(15))
summarization(runif(15), c("min", "max"))
summarization(runif(15), c("quantiles", "skewness"))