discretize: Discretize database via topdown greedy approach. Based on...
In diegomattozo/categorization: Categorization Of Continuous Variables.
Description
Usage
Arguments
Value
Description
Discretize database via topdown greedy approach. Based on discretization package created by HyunJi Kim.
Usage
1
discretize(db, meth = 4, alpha = 0.05, n = 30)
Arguments
db
database to discretize (data.frame)
meth
measures of associations available 1. Caim 2. Cacc 3. Ameva 4. Info. Statistics 5. Kendall's Tau-C
(numeric)
alpha
Penalization to limit number of categories. Only for methods 4 and 5. (numeric)
n
Desired Number of observations per Quantile.
Value
list with discretized data, vector of quantile cutpoints and the supervised method cutpoints.
diegomattozo/categorization documentation built on Sept. 26, 2020, 3:42 p.m.
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Description Usage Arguments Value
Description
Discretize database via topdown greedy approach. Based on discretization package created by HyunJi Kim.
Usage
1 | discretize(db, meth = 4, alpha = 0.05, n = 30)
|
Arguments
db |
database to discretize (data.frame) |
meth |
measures of associations available 1. Caim 2. Cacc 3. Ameva 4. Info. Statistics 5. Kendall's Tau-C (numeric) |
alpha |
Penalization to limit number of categories. Only for methods 4 and 5. (numeric) |
n |
Desired Number of observations per Quantile. |
Value
list with discretized data, vector of quantile cutpoints and the supervised method cutpoints.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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