Parents (Total: 4)

The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	DEDD7A3838CB9ADFCD7C692A3646E9B2
PackageArch	x86_64
PackageDescription	Implements 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.
PackageName	R-woeBinning
PackageRelease	lp153.2.3
PackageVersion	0.1.6
SHA-1	9115279CC30FADCD84855A908603CE95447EBD1E
SHA-256	92DC3C42D4D5995022D44CCEC92358AE2998F53C2818058875F09E0E7DD2022F

Key	Value
MD5	C6B4C0CB6BD6A459E1450E00E6858922
PackageArch	x86_64
PackageDescription	Implements 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.
PackageName	R-woeBinning
PackageRelease	2.19
PackageVersion	0.1.6
SHA-1	234CE22222244B1BB5C17533E33C0CD5D637286D
SHA-256	A645BA65B107EF8209A95D21D0E1B460605A6A5449427D4947B220E852317CDD

Key	Value
MD5	645E846F8725C29DE315721F512C67DF
PackageArch	x86_64
PackageDescription	Implements 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.
PackageName	R-woeBinning
PackageRelease	lp152.2.6
PackageVersion	0.1.6
SHA-1	17D31B51872D856B79A993A61AD979EC0E549E2D
SHA-256	33CA21AE4B5F2E2692B1014C2009DC2CCB3E29111BEDB02FF40E829895E84291

Key	Value
MD5	4BFB7DD87AE1455F0899EA67DC18ACF8
PackageArch	x86_64
PackageDescription	Implements 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.
PackageMaintainer	https://www.suse.com/
PackageName	R-woeBinning
PackageRelease	lp154.2.1
PackageVersion	0.1.6
SHA-1	A89C79501DFA4571CFDD98EA35E716413B43B154
SHA-256	E534133E1D5C5EA3928BEA89658D51BF7D073A539DEFD4FED98AA1FE3C82BCE7