Result for 3D2F045FF47E6D620E8274F77C8C726EC3435364

Query result

Key Value
FileName./usr/lib64/R/library/glmnet/R/glmnet.rdb
FileSize123425
MD52FC945C3B40D4EA2BFDDFF63EE30DA95
SHA-13D2F045FF47E6D620E8274F77C8C726EC3435364
SHA-2567A3020600D12FA76DFA4C2B009351C97D1BC5ED98ED2C20958DDE653BA6386C5
SSDEEP1536:z2Dsnrh3XVOQ7MAP05SiETAfDCRJr9R2U3vX9+K6hpxOwHwBIGexEucFShaSyX0M:+sdwAs5bg2UPwK+xOw4ehvA0rnOuTs
TLSHT1D0C313B299582E9DCBFD55041543777488AD4D2CEB2020F3478AE0B72838FF85BAE255
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
MD5A56DDEB85D20CF4A4C3B57E7793A4751
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
PackageRelease1.16
PackageVersion2.0.18
SHA-1B92BBAE52A44F6F081719708E20F12B25188E661
SHA-25678FA90A2A115F9EE723D58CFF00533C0CAFAEF24A9E5C8FC6C2EA09302B02A8C