Key | Value |
---|---|
FileName | ./usr/lib64/R/library/aweSOM/htmlwidgets/aweSOMwidget.yaml |
FileSize | 102 |
MD5 | 227D42356DAA5D6E1BFF8E727AFFBB5C |
SHA-1 | 002ABE58F7A3497CC7E57ED31A42D29F4B8AD4EA |
SHA-256 | 8ADEA1B99514AC2AC32983C8D18D7C3A13EBD08348621688BF0952F81DC9E596 |
SSDEEP | 3:hWlFIAzo/M2qeSj31A/gaVRtvFF/F9Qv:Wk/M2WA/gOdz6 |
TLSH | T1C2B01200DD06F275181100F7449D5221123B1247F004585638FEC1190F903D90154470 |
hashlookup:parent-total | 4 |
hashlookup:trust | 70 |
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 | 422C832ADA637A26587585EF2490AC12 |
PackageArch | x86_64 |
PackageDescription | Self-organizing maps (also known as SOM, see Kohonen (2001) <doi:10.1007/978-3-642-56927-2>) are a method for dimensionality reduction and clustering of continuous data. This package introduces interactive (html) graphics for easier analysis of SOM results. It also features an interactive interface, for push-button training and visualization of SOM on numeric, categorical or mixed data, as well as tools to evaluate the quality of SOM. |
PackageName | R-aweSOM |
PackageRelease | lp153.9.1 |
PackageVersion | 1.2 |
SHA-1 | D2DA342C89A4DDD23E644C1A5A0499A149476CC3 |
SHA-256 | CC2188990532BFF4DF5003613B232B87C98D14B29F9D51620CF3FC8C1A861AF4 |
Key | Value |
---|---|
MD5 | FC1AD930D9AB73D908FAA5C4960A7A76 |
PackageArch | x86_64 |
PackageDescription | Self-organizing maps (also known as SOM, see Kohonen (2001) <doi:10.1007/978-3-642-56927-2>) are a method for dimensionality reduction and clustering of continuous data. This package introduces interactive (html) graphics for easier analysis of SOM results. It also features an interactive interface, for push-button training and visualization of SOM on numeric, categorical or mixed data, as well as tools to evaluate the quality of SOM. |
PackageName | R-aweSOM |
PackageRelease | lp154.9.1 |
PackageVersion | 1.2 |
SHA-1 | 414797B8ECAB0CAB6105A17CADC9A4CC88501E41 |
SHA-256 | 5E1680784CA5CD8B3F6CD8381427631213EBBB2D4C15CC6E52238F4DB0E90954 |
Key | Value |
---|---|
MD5 | 5C2C06183E771A40FA011A821C9E58D5 |
PackageArch | x86_64 |
PackageDescription | Self-organizing maps (also known as SOM, see Kohonen (2001) <doi:10.1007/978-3-642-56927-2>) are a method for dimensionality reduction and clustering of continuous data. This package introduces interactive (html) graphics for easier analysis of SOM results. It also features an interactive interface, for push-button training and visualization of SOM on numeric, categorical or mixed data, as well as tools to evaluate the quality of SOM. |
PackageName | R-aweSOM |
PackageRelease | 9.1 |
PackageVersion | 1.2 |
SHA-1 | 74E9E2A7E8A2000878D283F136E4A1E004AB4F27 |
SHA-256 | A3FC14D5D47657B65297DAE9FF11FA8500E2BD6C34E296AAF41655C73271B106 |
Key | Value |
---|---|
MD5 | 835008CF4C47EC17A4B2F7F2A90A4B06 |
PackageArch | x86_64 |
PackageDescription | Self-organizing maps (also known as SOM, see Kohonen (2001) <doi:10.1007/978-3-642-56927-2>) are a method for dimensionality reduction and clustering of continuous data. This package introduces interactive (html) graphics for easier analysis of SOM results. It also features an interactive interface, for push-button training and visualization of SOM on numeric, categorical or mixed data, as well as tools to evaluate the quality of SOM. |
PackageName | R-aweSOM |
PackageRelease | lp152.9.1 |
PackageVersion | 1.2 |
SHA-1 | A0175D4B2CBF8DE0AF492704DD8457E99F54019B |
SHA-256 | B5C7A6CD00E9CD537482293F1D78EA341A23E6C82DC876F775AA81B11D0D9200 |