{
   "name": "iris",
   "title": "Iris",
   "resources": [
      {
         "path": "iris.arff",
         "pathType": "local",
         "name": "iris",
         "format": "arff",
         "encoding": "ISO-8859-1"
      },
      {
         "path": "iris.csv",
         "pathType": "local",
         "name": "iris",
         "format": "csv",
         "mediatype": "text/csv",
         "encoding": "ISO-8859-1",
         "dialect": {
            "delimiter": ",",
            "quoteChar": "\""
         },
         "schema": {
            "fields": [
               {
                  "name": "sepallength",
                  "type": "number",
                  "format": "default"
               },
               {
                  "name": "sepalwidth",
                  "type": "number",
                  "format": "default"
               },
               {
                  "name": "petallength",
                  "type": "number",
                  "format": "default"
               },
               {
                  "name": "petalwidth",
                  "type": "number",
                  "format": "default"
               },
               {
                  "name": "class",
                  "type": "string",
                  "format": "default"
               }
            ],
            "missingValues": [
               ""
            ]
         }
      }
   ],
   "readme": "The resources for this dataset can be found at https://www.openml.org/d/61\n\nAuthor: R.A. Fisher  \nSource: [UCI](https://archive.ics.uci.edu/ml/datasets/Iris) - 1936 - Donated by Michael Marshall  \nPlease cite:   \n\nIris Plants Database  \nThis is perhaps the best known database to be found in the pattern recognition literature.  Fisher's paper is a classic in the field and is referenced frequently to this day.  (See Duda & Hart, for example.)  The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant.  One class is     linearly separable from the other 2; the latter are NOT linearly separable from each other.\n\nPredicted attribute: class of iris plant.  \nThis is an exceedingly simple domain.  \n \n### Attribute Information:\n    1. sepal length in cm\n    2. sepal width in cm\n    3. petal length in cm\n    4. petal width in cm\n    5. class: \n       -- Iris Setosa\n       -- Iris Versicolour\n       -- Iris Virginica",
   "description": "The resources for this dataset can be found at https://www.openml.org/d/61\n\nAuthor: R.A. Fisher  \nSo",
   "licenses": [
      {
         "name": "ODC-PDDL",
         "path": "http://opendatacommons.org/licenses/pddl/",
         "title": "Open Data Commons Public Domain Dedication and License"
      }
   ]
}