Description Usage Arguments Details Value References See Also Examples
Itemset characterization features measure measure the distribution of values of both single attributes and pairs of attributes.
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... |
Further arguments passed to the summarization functions. |
x |
A data.frame contained only the input attributes. |
y |
A factor response vector with one label for each row/component of x. |
features |
A list of features names or |
summary |
A list of summarization functions or empty for all values. See
post.processing method to more information. (Default:
|
formula |
A formula to define the class column. |
data |
A data.frame dataset contained the input attributes and class. The details section describes the valid values for this group. |
The following features are allowed for this method:
Individual frequency of each attributes' value.
Correlation information of the two attributes' value pairs.
It is a two itemset computed using a predictive attribute and the target.
A list named by the requested meta-features.
Song, Q., Wang, G., & Wang, C. (2012). Automatic recommendation of classification algorithms based on data set characteristics. Pattern Recognition, 45(7), 2672-2689.
Wang, G., Song, Q., & Zhu, X. (2015). An improved data characterization method and its application in classification algorithm recommendation. Applied Intelligence, 43(4), 892-912.
Other meta-features:
clustering()
,
complexity()
,
concept()
,
general()
,
infotheo()
,
landmarking()
,
model.based()
,
relative()
,
statistical()
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