{
    "data_id": "486",
    "name": "papir_1",
    "exact_name": "papir_1",
    "version": 1,
    "version_label": null,
    "description": "**Author**: Magne Aldrin (magne.aldrin@nr.no)  \n**Source**: [StatLib](http:\/\/lib.stat.cmu.edu\/datasets\/) - April 14. 1999  \n**Please cite**:   \n\nOne of two multivariate regression data sets from paper industry, from an experiment at the paper plant Norske Skog, Skogn, Norway. They have been described and analysed in:  \nAldrin, M. (1996), \"Moderate projection pursuit regression for multivariate response data\", Computational Statistics and Data Analysis,\n21, p. 501-531.\n\nIt consists of 30 observations (rows) and 22 variables (columns), but all response variables are missing for the 28th observation. Columns 1 to 13 are response variables that describes various qualities of the paper. Columns 14 to 22 are 9 predictor variables. The first three predictor variables (x1 in column 14, x2 in column 15 and x3 in column 16) were varied systematically through the experiment, taking the values 1, 0 and -1. The next three predictor variables (columns 17 to 19) are constructed as x1**2, x2**2 and x3**2. The last three predictor variables (columns 20 to 22) are constructed as x1*x2, x1*x3 and x2*x3.",
    "format": "ARFF",
    "uploader": "Joaquin Vanschoren",
    "uploader_id": 2,
    "visibility": "public",
    "creator": null,
    "contributor": null,
    "date": "2014-09-29 00:05:21",
    "update_comment": "fixed missing value characters",
    "last_update": "2015-04-15 22:13:37",
    "licence": "Public",
    "status": "active",
    "error_message": null,
    "url": "https:\/\/www.openml.org\/data\/download\/1390069\/phpLG8KFe",
    "default_target_attribute": "response_1",
    "row_id_attribute": null,
    "ignore_attribute": null,
    "runs": 0,
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            "papir_1",
            "One of two multivariate regression data sets from paper industry, from an experiment at the paper plant Norske Skog, Skogn, Norway. They have been described and analysed in: Aldrin, M. (1996), \"Moderate projection pursuit regression for multivariate response data\", Computational Statistics and Data Analysis, 21, p. 501-531. It consists of 30 observations (rows) and 22 variables (columns), but all response variables are missing for the 28th observation. Columns 1 to 13 are response variables that "
        ],
        "weight": 5
    },
    "qualities": [],
    "tags": [],
    "features": [
        {
            "name": "response_1",
            "index": "0",
            "type": "numeric",
            "distinct": "9",
            "missing": "1",
            "target": "1",
            "min": "31",
            "max": "35",
            "mean": "33",
            "stdev": "1"
        },
        {
            "name": "response_2",
            "index": "1",
            "type": "numeric",
            "distinct": "20",
            "missing": "1",
            "min": "29",
            "max": "34",
            "mean": "31",
            "stdev": "1"
        },
        {
            "name": "response_3",
            "index": "2",
            "type": "numeric",
            "distinct": "23",
            "missing": "1",
            "min": "5",
            "max": "9",
            "mean": "7",
            "stdev": "1"
        },
        {
            "name": "response_4",
            "index": "3",
            "type": "numeric",
            "distinct": "23",
            "missing": "1",
            "min": "6",
            "max": "10",
            "mean": "8",
            "stdev": "1"
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        {
            "name": "response_5",
            "index": "4",
            "type": "numeric",
            "distinct": "10",
            "missing": "1",
            "min": "13",
            "max": "17",
            "mean": "15",
            "stdev": "1"
        },
        {
            "name": "response_6",
            "index": "5",
            "type": "numeric",
            "distinct": "10",
            "missing": "1",
            "min": "11",
            "max": "14",
            "mean": "12",
            "stdev": "1"
        },
        {
            "name": "response_7",
            "index": "6",
            "type": "numeric",
            "distinct": "22",
            "missing": "1",
            "min": "8",
            "max": "12",
            "mean": "10",
            "stdev": "1"
        },
        {
            "name": "response_8",
            "index": "7",
            "type": "numeric",
            "distinct": "22",
            "missing": "1",
            "min": "16",
            "max": "20",
            "mean": "18",
            "stdev": "1"
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        {
            "name": "response_9",
            "index": "8",
            "type": "numeric",
            "distinct": "26",
            "missing": "1",
            "min": "20",
            "max": "25",
            "mean": "23",
            "stdev": "1"
        },
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            "name": "response_10",
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            "type": "numeric",
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            "missing": "1",
            "min": "15",
            "max": "20",
            "mean": "17",
            "stdev": "1"
        },
        {
            "name": "response_11",
            "index": "10",
            "type": "numeric",
            "distinct": "19",
            "missing": "1",
            "min": "20",
            "max": "23",
            "mean": "22",
            "stdev": "1"
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            "name": "response_12",
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            "missing": "1",
            "min": "87",
            "max": "92",
            "mean": "90",
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            "name": "response_13",
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            "missing": "1",
            "min": "22",
            "max": "26",
            "mean": "24",
            "stdev": "1"
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            "name": "x1",
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            "type": "nominal",
            "distinct": "3",
            "missing": "0",
            "distr": []
        },
        {
            "name": "x2",
            "index": "14",
            "type": "nominal",
            "distinct": "3",
            "missing": "0",
            "distr": []
        },
        {
            "name": "x3",
            "index": "15",
            "type": "nominal",
            "distinct": "3",
            "missing": "0",
            "distr": []
        },
        {
            "name": "x1**2",
            "index": "16",
            "type": "nominal",
            "distinct": "2",
            "missing": "0",
            "distr": []
        },
        {
            "name": "x2**2",
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            "type": "nominal",
            "distinct": "2",
            "missing": "0",
            "distr": []
        },
        {
            "name": "x3**2",
            "index": "18",
            "type": "nominal",
            "distinct": "2",
            "missing": "0",
            "distr": []
        },
        {
            "name": "x1*x2",
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            "type": "nominal",
            "distinct": "3",
            "missing": "0",
            "distr": []
        },
        {
            "name": "x2*x3",
            "index": "20",
            "type": "nominal",
            "distinct": "3",
            "missing": "0",
            "distr": []
        },
        {
            "name": "x3*x2",
            "index": "21",
            "type": "nominal",
            "distinct": "3",
            "missing": "0",
            "distr": []
        }
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    "nr_of_issues": 0,
    "nr_of_downvotes": 0,
    "nr_of_likes": 0,
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