{ "_id": "6a25193e4b233be19838cde7", "Package": "ICompELM", "Type": "Package", "Title": "Independent Component Analysis Based Extreme Learning Machine", "Version": "0.1.0", "Authors@R": "c(person(\"Saikath\", \"Das\", role = c(\"aut\", \"cre\"),\nemail = \"saikathdas007@gmail.com\"),\nperson(\"Ranjit Kumar\", \"Paul\", role = \"aut\"),\nperson(\"Md\", \"Yeasin\", role = \"aut\"),\nperson(\"Amrit Kumar\", \"Paul\", role = \"aut\"))", "Description": "Single Layer Feed-forward Neural networks (SLFNs) have\nmany applications in various fields of statistical modelling,\nespecially for time-series forecasting. However, there are some\nmajor disadvantages of training such networks via the widely\naccepted 'gradient-based backpropagation' algorithm, such as\nconvergence to local minima, dependencies on learning rate and\nlarge training time. These concerns were addressed by Huang et\nal. (2006) , wherein they\nintroduced the Extreme Learning Machine (ELM), an extremely\nfast learning algorithm for SLFNs which randomly chooses the\nweights connecting input and hidden nodes and analytically\ndetermines the output weights of SLFNs. It shows good\ngeneralized performance, but is still subject to a high degree\nof randomness. To mitigate this issue, this package uses a\ndimensionality reduction technique given in Hyvarinen (1999)\n, namely, the Independent Component\nAnalysis (ICA) to determine the input-hidden connections and\nthus, remove any sort of randomness from the algorithm. This\nleads to a robust, fast and stable ELM model. Using functions\nwithin this package, the proposed model can also be compared\nwith an existing alternative based on the Principal Component\nAnalysis (PCA) algorithm given by Pearson (1901)\n, i.e., the PCA based ELM model\ngiven by Castano et al. (2013) ,\nfrom which the implemented ICA based algorithm is greatly\ninspired.", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.3.1", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-07 07:05:57 UTC", "User": "root" }, "Author": "Saikath Das [aut, cre], Ranjit Kumar Paul [aut], Md Yeasin\n[aut], Amrit Kumar Paul [aut]", "Maintainer": "Saikath Das ", "Config/pak/sysreqs": "cmake texlive libssl-dev", "Repository": "https://saikathd.r-universe.dev", "Date/Publication": "2024-06-11 02:42:17 UTC", "RemoteUrl": "https://github.com/cran/ICompELM", "RemoteRef": "HEAD", "RemoteSha": "f4ce1eed58cb94d4e4f359824ae1fbe64cc87ec4", "MD5sum": "807805e42d8243af914148b51a28db8c", "_user": "saikathd", "_type": "src", "_file": "ICompELM_0.1.0.tar.gz", "_fileid": "16187375b2fdb7ec7a6b069c1607b6ef4375f0cb8e79efaa6965dda324f0041f", "_filesize": 174805, "_sha256": "16187375b2fdb7ec7a6b069c1607b6ef4375f0cb8e79efaa6965dda324f0041f", "_created": "2026-06-07T07:05:57.000Z", 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