{ "_id": "6a1d37fa1d7bb097a0a3dc61", "Package": "multiclassPairs", "Type": "Package", "Title": "Build MultiClass Pair-Based Classifiers using TSPs or RF", "Version": "0.4.3", "Author": "Nour-al-dain Marzouka", "Maintainer": "Nour-al-dain Marzouka ", "Description": "A toolbox to train a single sample classifier that uses\nin-sample feature relationships. The relationships are\nrepresented as feature1 < feature2 (e.g. gene1 < gene2). We\nprovide two options to go with. First is based on 'switchBox'\npackage which uses Top-score pairs algorithm. Second is a novel\nimplementation based on random forest algorithm. For simple\nproblems we recommend to use one-vs-rest using TSP option due\nto its simplicity and for being easy to interpret. For complex\nproblems RF performs better. Both lines filter the features\nfirst then combine the filtered features to make the list of\nall the possible rules (i.e. rule1: feature1 < feature2, rule2:\nfeature1 < feature3, etc...). Then the list of rules will be\nfiltered and the most important and informative rules will be\nkept. The informative rules will be assembled in an one-vs-rest\nmodel or in an RF model. We provide a detailed description\nwith each function in this package to explain the filtration\nand training methodology in each line. Reference: Marzouka &\nEriksson (2021) .", "URL": "https://github.com/NourMarzouka/multiclassPairs", "License": "GPL (>= 2)", "Encoding": "UTF-8", "biocViews": "Classification", "RoxygenNote": "7.1.1", "VignetteBuilder": "knitr", "Config/pak/sysreqs": "libicu-dev libclang-dev", "Repository": "https://nourmarzouka.r-universe.dev", "Date/Publication": "2023-05-01 13:48:40 UTC", "RemoteUrl": "https://github.com/nourmarzouka/multiclasspairs", "RemoteRef": "HEAD", "RemoteSha": "6c4d9d73c2debf8603df5734c30ea1babe4d47d0", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-01 07:34:47 UTC", "User": "root" }, "MD5sum": "826e5ddf51746bff4c908ef9f0aca0b6", "_user": "nourmarzouka", "_type": "src", "_file": "multiclassPairs_0.4.3.tar.gz", "_fileid": "591b0c7b9e7fedf3f351f6cf8916b40b569a3579f605163fe2cf4e4d49c15208", "_filesize": 2772713, "_sha256": "591b0c7b9e7fedf3f351f6cf8916b40b569a3579f605163fe2cf4e4d49c15208", "_created": "2026-06-01T07:34:47.000Z", "_published": "2026-06-01T07:42:50.497Z", "_distro": "noble", "_jobs": [ { "job": 78806512241, "time": 219, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "NOTE", "artifact": "7325838506" }, { "job": 78806512277, "time": 203, "config": "linux-release-x86_64", "r": "4.6.0", "check": "NOTE", "artifact": "7325833794" }, { "job": 78806512276, "time": 220, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "NOTE", "artifact": "7325863895" }, { "job": 78806512251, "time": 170, "config": "macos-release-arm64", "r": "4.6.0", "check": "NOTE", "artifact": "7325859998" }, { "job": 78805953013, "time": 247, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7325777304" }, { "job": 78806512242, "time": 164, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7325822549" }, { "job": 78806512279, "time": 184, "config": "windows-devel", "r": "4.7.0", "check": "NOTE", "artifact": "7325828452" }, { "job": 78806512244, "time": 145, "config": "windows-oldrel", "r": "4.5.3", 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"predict_RF", "proximity_matrix_RF", "ReadData", "sort_genes_RF", "sort_rules_RF", "summary_genes_RF", "train_one_vs_rest_TSP", "train_RF" ], "_help": [ { "page": "do_dunn_test", "title": "internal function", "topics": [ "do_dunn_test" ] }, { "page": "filter_genes_TSP", "title": "Filter genes/features for multiclass one-vs-rest classifier downstream training", "topics": [ "filter_genes_TSP" ] }, { "page": "group_TSP", "title": "Internal function: for grouping labels for one-vs-rest usage", "topics": [ "group_TSP" ] }, { "page": "optimize_RF", "title": "Optimize parameters to be used in training the final RF model", "topics": [ "optimize_RF" ] }, { "page": "plot_binary_RF", "title": "Plot binary rule-based heatmaps", "topics": [ "plot_binary_RF" ] }, { "page": "plot_binary_TSP", "title": "Plot binary rule-based heatmaps", "topics": [ "plot_binary_TSP" ] }, { "page": "predict_one_vs_rest_TSP", "title": "Predict sample class based on one-vs-rest multiclass top score pairs classifier", "topics": [ "predict_one_vs_rest_TSP" ] }, { "page": "predict_RF", "title": "Predict sample class based on gene pair-based random forest classifier", "topics": [ "predict_RF" ] }, { "page": "print-methods", "title": "Methods for Function 'print' in Package 'multiclassPairs'", "topics": [ "print,multiclassPairs_object-method", "print,OnevsrestScheme_genes_SB-method", "print,OnevsrestScheme_SB-method", "print,RandomForest_sorted_genes-method", "print,RandomForest_sorted_rules-method", "print,rule_based_RandomForest-method", "print-methods" ] }, { "page": "proximity_matrix_RF", "title": "Plot binary rule-based heatmaps", "topics": [ "proximity_matrix_RF" ] }, { "page": "ReadData", "title": "Function for preparing data object", "topics": [ "ReadData" ] }, { "page": "sort_genes_RF", "title": "Sort genes/features for pair-based random forest classifier downstream steps", "topics": [ "sort_genes_RF" ] }, { "page": "sort_rules_RF", "title": "Create and sort feature/gene pairs for pair-based random forest classifier training step", "topics": [ "sort_rules_RF" ] }, { "page": "summary_genes_RF", "title": "Summarize sorted genes to rules", "topics": [ "summary_genes_RF" ] }, { "page": "train_one_vs_rest_TSP", "title": "Build multiclass rule-based classifier as one-vs-rest scheme", "topics": [ "train_one_vs_rest_TSP" ] }, { "page": "train_RF", "title": "Train pair-based random forest model", "topics": [ "train_RF" ] } ], "_readme": "https://github.com/nourmarzouka/multiclasspairs/raw/HEAD/README.md", "_rundeps": [ "Boruta", "ca", "caret", "class", "cli", "clock", "cluster", "codetools", "colorspace", "corrr", "cpp11", "data.table", "diagram", "digest", "dplyr", "dunn.test", "e1071", "farver", "foreach", "fru", "future", "future.apply", "gclus", "generics", "ggplot2", "ggrepel", "globals", "glue", "gower", "gtable", "hardhat", "ipred", "isoband", "iterators", "KernSmooth", "labeling", "lattice", "lava", "lifecycle", "listenv", "lubridate", "magrittr", "MASS", "Matrix", "mgcv", 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