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  "Description": "Extends the 'mlr3' package and ecosystem to time series\nforecasting. Provides forecasting tasks, learners, resampling\nstrategies, performance measures, and 'mlr3pipelines' operators\nfor time-series feature engineering. Machine learning\nregression learners can be turned into forecasters through\nrecursive and direct multi-step strategies.",
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      "title": "Multiple-Seasonal ARIMA Forecast Learner",
      "concept": [
        "Learner"
      ],
      "topics": [
        "LearnerFcstMsarima",
        "mlr_learners_fcst.msarima"
      ]
    },
    {
      "page": "mlr_learners_fcst.nnetar",
      "title": "Neural Network Forecast Learner",
      "concept": [
        "Learner"
      ],
      "topics": [
        "LearnerFcstNnetar",
        "mlr_learners_fcst.nnetar"
      ]
    },
    {
      "page": "mlr_learners_fcst.prophet",
      "title": "Prophet Forecast Learner",
      "concept": [
        "Learner"
      ],
      "topics": [
        "LearnerFcstProphet",
        "mlr_learners_fcst.prophet"
      ]
    },
    {
      "page": "mlr_learners_fcst.random_walk",
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        "mlr_learners_fcst.random_walk"
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    },
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      "page": "mlr_learners_fcst.rlgt",
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        "mlr_learners_fcst.rlgt"
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    },
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        "mlr_learners_fcst.ssarima"
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    },
    {
      "page": "mlr_learners_fcst.stlm",
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        "mlr_learners_fcst.stlm"
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    },
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    },
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        "mlr_learners_fcst.tbats"
      ]
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      "page": "mlr_learners_fcst.theta",
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        "Learner"
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        "mlr_learners_fcst.theta"
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      "page": "mlr_learners_fcst.tscount",
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      ],
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        "mlr_learners_fcst.tscount"
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    },
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      "page": "mlr_learners_fcst.tslm",
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        "mlr_learners_fcst.tslm"
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        "mlr_measures_fcst.acf1"
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      "page": "mlr_measures_fcst.mase",
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        "mlr_measures_fcst.mase"
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    },
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    },
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      "page": "mlr_pipeops_fcstavg",
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    {
      "page": "mlr_tasks_airpassengers",
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