Result for 0E4ED6A5FAF7C65157F90705A874C73839B7AA05

Query result

Key Value
FileName./usr/lib64/root/libTMVA.so.5.34
FileSize27413283
MD5EA6342960AC18D1C98464143AA51E4E0
SHA-10E4ED6A5FAF7C65157F90705A874C73839B7AA05
SHA-2565A1C61CB856B35BB6F45832D3D0E02F2DAE8965008AC84E234D4B46FB2E030D4
SSDEEP196608:zuazAgMZU21vZpjq7MVkJE5pCpEkG6RARrVKQ/W8xrDMEA1MbNKZH5FQrUBFjqU/:zxvvgpjZ/pCpvRc0Q/W8xrDMkj8
TLSHT178578C1EFF518C49CACDEBB8A8EF1F292F90E4C5EA17135B4158A4701FD23191F4A16A
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
MD506B1455388AB5205B4998C7E0089D76F
PackageArchx86_64
PackageDescriptionThe Toolkit for Multivariate Analysis (TMVA) provides a ROOT-integrated environment for the parallel processing and evaluation of MVA techniques to discriminate signal from background samples. It presently includes (ranked by complexity): * Rectangular cut optimization * Correlated likelihood estimator (PDE approach) * Multi-dimensional likelihood estimator (PDE - range-search approach) * Fisher (and Mahalanobis) discriminant * H-Matrix (chi-squared) estimator * Artificial Neural Network (two different implementations) * Boosted Decision Trees The TMVA package includes an implementation for each of these discrimination techniques, their training and testing (performance evaluation). In addition all these methods can be tested in parallel, and hence their performance on a particular data set may easily be compared.
PackageMaintainerFedora Project
PackageNameroot-tmva
PackageRelease1.el5
PackageVersion5.34.36
SHA-19844E29843567EADF05031748AF1878C653660F2
SHA-2561E978E343845DA4E0B2BCE01E3C7878246D9BA6A2B1BA36D2FFC9541560146FE