finco {dprep} | R Documentation |
This function selects features using the FINCO algorithm. The dataset must contain only discretized values.
finco(data, level)
data |
name of the dataset containing the discretized values |
level |
minimum inconsistency level |
The level value must be greater than the inconsistency of the whole dataset, which first must be discretized. The function inconsist included in this library computes inconsistencies. A small value of level yields a greater number of selected features.
varselec |
index of selected features |
inconsis |
inconsistency rates of the selected features |
Edgar Acuna
Acuna, E , (2003) A comparison of filters and wrappers for feature selection in supervised classification. Proceedings of the Interface 2003 Computing Science and Statistics. Vol 34.
Acuna, E., Coaquira, F. and Gonzalez, M. (2003). A comparison of feature selection procedures for classifiers based on kernel density estimation. Proc. of the Int. Conf. on Computer, Communication and Control technologies, CCCT03. VolI. p. 468-472. Orlando, Florida.
#---- Feature Selection with FINCO data(my.iris) disciris=disc.ew(my.iris,1:6) inconsist(disciris) finco(disciris,0.05)