Key | Value |
---|---|
FileName | ./usr/lib64/R/library/aweSOM/help/AnIndex |
FileSize | 290 |
MD5 | D9D94254A24CF4CD39C3CE926A35F2D9 |
SHA-1 | 2765788CBFC0EE9E3CE6696EF85DA86445E8542A |
SHA-256 | FBF87E06C6145C7B646998614FE9AB5E71280495A2E7A63780FE44C200987C63 |
SSDEEP | 6:fqurRrfzQqiXhoiXh8NIbz8AcAuEBQAws+QAwqMvZ9sFLMI0IE5e:XtjtiXGiXDbzf3wFwqdFiVs |
TLSH | T1D4D01757585403DB92CB5C8237D5AD0CABD8B83220AA6243120391FCB6CFF9CCA9B830 |
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 |