{
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  "Title": "Optimal Trees Ensembles for Regression, Classification and Class\nMembership Probability Estimation",
  "Version": "1.0.1",
  "Date": "2020-04-18",
  "Author": "Zardad Khan, Asma Gul, Aris Perperoglou, Osama Mahmoud, Werner\nAdler, Miftahuddin and Berthold Lausen",
  "Maintainer": "Zardad Khan <zardadkhan@awkum.edu.pk>",
  "Description": "Functions for creating ensembles of optimal trees for\nregression, classification (Khan, Z., Gul, A., Perperoglou, A.,\nMiftahuddin, M., Mahmoud, O., Adler, W., & Lausen, B. (2019).\n(2019) <doi:10.1007/s11634-019-00364-9>) and class membership\nprobability estimation (Khan, Z, Gul, A, Mahmoud, O,\nMiftahuddin, M, Perperoglou, A, Adler, W & Lausen, B (2016)\n<doi:10.1007/978-3-319-25226-1_34>) are given. A few trees are\nselected from an initial set of trees grown by random forest\nfor the ensemble on the basis of their individual and\ncollective performance. Three different methods of tree\nselection for the case of classification are given. The\nprediction functions return estimates of the test responses and\ntheir class membership probabilities. Unexplained variations,\nerror rates, confusion matrix, Brier scores, etc. are also\nreturned for the test data.",
  "License": "GPL (>= 3)",
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      "title": "Prediction function for the object returned by 'OTReg'",
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