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  "Title": "Gaussian Mixture Modeling Algorithms and the Belief-Based\nMixture Modeling",
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  "Description": "Two partially supervised mixture modeling methods:\nsoft-label and belief-based modeling are implemented. For\ncompleteness, we equipped the package also with the\nfunctionality of unsupervised, semi- and fully supervised\nmixture modeling.  The package can be applied also to selection\nof the best-fitting from a set of models with different\ncomponent numbers or constraints on their structures. For\ndetailed introduction see: Przemyslaw Biecek, Ewa Szczurek,\nMartin Vingron, Jerzy Tiuryn (2012), The R Package bgmm:\nMixture Modeling with Uncertain Knowledge, Journal of\nStatistical Software <doi:10.18637/jss.v047.i03>.",
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    "softList",
    "supervised",
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        "bgmm"
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    },
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      "title": "Data for clustering of 384 cell cycle genes into five clusters corresponding to cell cycle phases",
      "topics": [
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        "CellCycleBeliefs",
        "CellCycleCenters",
        "CellCycleClass",
        "CellCycleData"
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