LocalRecProg | R Documentation |
To be used on both categorical and numeric input variables, although usage on categorical variables is the focus of the development of this software.
LocalRecProg(
obj,
ancestors = NULL,
ancestor_setting = NULL,
k_level = 2,
FindLowestK = TRUE,
weight = NULL,
lowMemory = FALSE,
missingValue = NA,
...
)
obj |
a |
ancestors |
Names of ancestors of the cateorical variables |
ancestor_setting |
For each ancestor the corresponding categorical variable |
k_level |
Level for k-anonymity |
FindLowestK |
requests the program to look for the smallest k that results in complete matches of the data. |
weight |
A weight for each variable (Default=1) |
lowMemory |
Slower algorithm with less memory consumption |
missingValue |
The output value for a suppressed value. |
... |
see arguments below
|
Each record in the data represents a category of the original data, and hence all records in the input data should be unique by the N Input Variables. To achieve bigger category sizes (k-anoymity), one can form new categories based on the recoding result and repeatedly apply this algorithm.
dataframe with original variables and the supressed variables
(suffix _lr). / the modified sdcMicroObj-class
Alexander Kowarik, Bernd Prantner, IHSN C++ source, Akimichi Takemura
Kowarik, A. and Templ, M. and Meindl, B. and Fonteneau, F. and Prantner, B.: Testing of IHSN Cpp Code and Inclusion of New Methods into sdcMicro, in: Lecture Notes in Computer Science, J. Domingo-Ferrer, I. Tinnirello (editors.); Springer, Berlin, 2012, ISBN: 978-3-642-33626-3, pp. 63-77. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/978-3-642-33627-0_6")}
data(testdata2)
cat_vars <- c("urbrur", "roof", "walls", "water", "sex", "relat")
anc_var <- c("water2", "water3", "relat2")
anc_setting <- c("water","water","relat")
r1 <- LocalRecProg(
obj = testdata2,
categorical = cat_vars,
missingValue = -99)
r2 <- LocalRecProg(
obj = testdata2,
categorical = cat_vars,
ancestor = anc_var,
ancestor_setting = anc_setting,
missingValue = -99)
r3 <- LocalRecProg(
obj = testdata2,
categorical = cat_vars,
ancestor = anc_var,
ancestor_setting = anc_setting,
missingValue = -99,
FindLowestK = FALSE)
# for objects of class sdcMicro:
sdc <- createSdcObj(
dat = testdata2,
keyVars = c("urbrur", "roof", "walls", "water", "electcon", "relat", "sex"),
numVars = c("expend", "income", "savings"),
w = "sampling_weight")
sdc <- LocalRecProg(sdc)
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