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The\npossible options for optimization algorithms are RMSprop, Adam\nand SGD with momentum. The package contains a vectorized C++\nimplementation that facilitates fast training through\nmini-batch learning.", "License": "GPL (>= 3) | file LICENSE", "URL": "https://github.com/bflammers/ANN2", "Encoding": "UTF-8", "SystemRequirements": "C++17", "RoxygenNote": "7.3.3", "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev", "Repository": "https://bflammers.r-universe.dev", "Date/Publication": "2025-10-09 19:38:54 UTC", "RemoteUrl": "https://github.com/bflammers/ann2", "RemoteRef": "HEAD", "RemoteSha": "5c4d018c29078c2b6aaf1476e4ca6c4ffb8dc1f3", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-05-12 08:20:06 UTC", "User": "root" }, "Author": "Bart Lammers [aut, cre]", "MD5sum": "1c871617b087f03da8d8d86effe6505a", "_user": "bflammers", "_type": "src", "_file": "ANN2_2.4.0.tar.gz", "_fileid": "9656d7eb209c63976754a8563beeacb1161bb5fb17a2d4e55ac045eb13993f95", "_filesize": 392568, "_sha256": "9656d7eb209c63976754a8563beeacb1161bb5fb17a2d4e55ac045eb13993f95", "_created": 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