Result for 158036C8FE6829EDFED89069164C749BDFD43EF9

Query result

Key Value
FileName./usr/lib64/R/library/glmnet/R/glmnet.rdb
FileSize123424
MD538DF5C820D03028E9B7D9B6D0DF1CB30
SHA-1158036C8FE6829EDFED89069164C749BDFD43EF9
SHA-256A69FC63A0D6AF91BB6645427A86A9230001BBDE3D64C3C7C3F10CB1B35A68210
SSDEEP1536:z2csnrT3XVOQ7MAP05SiETAfDCRJr9R2U3vX9+K6hpxOwHwBIGexEucFShaSyX0M:tsbwAs5bg2UPwK+xOw4ehvA0rnOuTs
TLSHT15AC313B29D582E9DCBFD55041583677484AD4D2CFB2420F34786E0BB2838FF85BAB255
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
MD5EE0153416AAC7A8581C323493E5F5BAB
PackageArchx86_64
PackageDescriptionExtremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. Two recent additions are the multiple-response Gaussian, and the grouped multinomial regression. The algorithm uses cyclical coordinate descent in a path-wise fashion.
PackageNameR-glmnet
PackageRelease1.6
PackageVersion2.0.18
SHA-1123B4F47FFA9E4A849CD7B1B4FFE28C07A448558
SHA-256FC94C8CF0E37BC2384EF8C32FD200D7F665A11A02D83FC6FF4F92EF442111674