RapidMiner Community Edition 9.8.1 freeware
RapidMiner is the world-wide leading data mining solution due to the combination of its functional range and its leading-edge technologies. Applications of RapidMiner have a wide spread in data mining all over the world.
Author | Rapid-I GmbH |
Released | 2020-12-03 |
Filesize | 277.00 MB |
Downloads | 127 |
OS | Windows XP, Windows Vista, Windows 7, Windows 8, Windows 10 |
Installation | Instal And Uninstall |
Keywords | data miner, business intelligence, data analyzer, analyzer, analyze, checker |
Users' rating (7 rating) |
RapidMiner Community Edition Free Download - we do not host any RapidMiner Community Edition torrent files or links of RapidMiner Community Edition on rapidshare.com, depositfiles.com, megaupload.com etc. All RapidMiner Community Edition download links are direct RapidMiner Community Edition download from publisher site or their selected mirrors.
9.8.1 | Dec 3, 2020 | New Release | New Features: Added new operators to delete data from Azure Cloud: Delete Azure Blob Storage Resource Delete Azure Data Lake Storage Resource Delete Azure Data Lake Storage Gen2 Resource Enhancements: All Loop cloud operators (e.g. Loop Amazon S3, Loop Azure Blob Storage, etc) now only download a file when another operator reads its content. The memory footprint may also decrease by 50%, and unnecessary writes to the disk are avoided. Bugfixes: Continue RapidMiner Studio start if proxy discovery fails Added missing Cluster attribute to metadata when applying a KMeans model via Apply Model Fixed a regression in Generalized Linear Model (GLM) model training. It again accepts weighted training data Auto Model Clustering showed incorrect results, ignoring training data normalization and attribute reordering Fixed AbstractMethodError when using very old JDBC drivers (built for Java 6 and earlier) to connect to SQL databases. |
9.8.0 | Oct 14, 2020 | New Release | New Features: Utilize AI Hub 9.8 support for large files in Projects. Files with more than 10MB and stored ExampleSets are automatically handled to be versioned as expected, but stored more efficiently. This is backed by Git LFS, which means Python or R coders can continue to easily work with these projects as long as they have the Git LFS extension installed. Time Series Windowing Update: Added time based (window parameters are specified in time units) and custom windowing (start and stop values of the windows are provided by an additional example set) for all windowing operators (Windowing, Process Windows, Forecast Validation, Sliding Window Validation) Added a few more parameters: expert settings (couples a few expert parameters into not shown, if it is not selected), windows defined (specifies from which point windows are defined), empty window handling. |
9.7.1 | Jun 24, 2020 | New Release |