Result for 00E4FA460B34A6474CA9FC492652FC616D8881E4

Query result

Key Value
FileName./usr/lib64/R/library/woeBinning/R/woeBinning.rdb
FileSize68858
MD528DBC46BA86F5FD0EB6153BD9AD51C56
SHA-100E4FA460B34A6474CA9FC492652FC616D8881E4
SHA-256DB0FD7178058E4FDDAD8DDD96B81DE961BFB0064DD2C4132C157B8C6D01BBD65
SSDEEP1536:zqgYey3XsjN5Y+U12szeoyvb9JXjq+ddVbjm4OMY3FIR2N7hdmYOGC3p4E7Kvl:P7BN5Y+U1/eoyxU+RYmR2NnmYZEed
TLSHT11D6302D41ACC1A6178A1995092239BB089FAC9F06BF748EE923CC7A0397453BA3358C5
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD54BFB7DD87AE1455F0899EA67DC18ACF8
PackageArchx86_64
PackageDescriptionImplements an automated binning of numeric variables and factors with respect to a dichotomous target variable. Two approaches are provided: An implementation of fine and coarse classing that merges granular classes and levels step by step. And a tree-like approach that iteratively segments the initial bins via binary splits. Both procedures merge, respectively split, bins based on similar weight of evidence (WOE) values and stop via an information value (IV) based criteria. The package can be used with single variables or an entire data frame. It provides flexible tools for exploring different binning solutions and for deploying them to (new) data.
PackageMaintainerhttps://www.suse.com/
PackageNameR-woeBinning
PackageReleaselp154.2.1
PackageVersion0.1.6
SHA-1A89C79501DFA4571CFDD98EA35E716413B43B154
SHA-256E534133E1D5C5EA3928BEA89658D51BF7D073A539DEFD4FED98AA1FE3C82BCE7