| RenDim {IDmining} | R Documentation |
Renyi's Generalized Dimensions
Description
Estimates Rényi's generalized dimensions (or Rényi's dimensions of qth order). It is
mainly for q=2 that the result is used as an estimate of the intrinsic dimension of data.
Usage
RenDim(X, scaleQ=1:5, qMin=2, qMax=2)
Arguments
X |
A |
scaleQ |
A vector (at least two values). It contains the values of |
qMin |
The minimum value of |
qMax |
The maximum value of |
Details
-
\ellis the edge length of the grid cells (or quadrats). Since the variables (and consenquently the grid) are rescaled to the[0,1]interval,\ellis equal to1for a grid consisting of only one cell. -
\ell^{-1}is the number of grid cells (or quadrats) along each axis of the Euclidean space in which the data points are embedded. -
\ell^{-1}is equal toQ^{(1/E)}whereQis the number of grid cells andEis the number of variables (or features). -
\ell^{-1}is directly related to\delta(see References). -
\deltais the diagonal length of the grid cells.
Value
A list of two elements:
a
data.framecontaining the value of Rényi's information ofqthorder (computed using the natural logarithm) for each value of\ln (\delta)andq. The values of\ln (\delta)are provided with regard to the[0,1]interval.a
data.framecontaining the value ofD_qfor each value ofq.
Author(s)
Jean Golay jeangolay@gmail.com
References
C. Traina Jr., A. J. M. Traina, L. Wu and C. Faloutsos (2000). Fast feature selection using fractal dimension. Proceedings of the 15th Brazilian Symposium on Databases (SBBD 2000), João Pessoa (Brazil).
E. P. M. De Sousa, C. Traina Jr., A. J. M. Traina, L. Wu and C. Faloutsos (2007). A fast and effective method to find correlations among attributes in databases, Data Mining and Knowledge Discovery 14(3):367-407.
J. Golay and M. Kanevski (2015). A new estimator of intrinsic dimension based on the multipoint Morisita index, Pattern Recognition 48 (12):4070–4081.
H. Hentschel and I. Procaccia (1983). The infinite number of generalized dimensions of fractals and strange attractors, Physica D 8(3):435-444.
Examples
sim_dat <- SwissRoll(1000)
scaleQ <- 1:15 # It starts with a grid of 1^E cell (or quadrat).
# It ends with a grid of 15^E cells (or quadrats).
qRI_ID <- RenDim(sim_dat[,c(1,2)], scaleQ[5:15])
print(paste("The ID estimate is equal to",round(qRI_ID[[1]][1,2],2)))