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| KEEL-dataset - data set description |
This section describes main characteristics of the iris data set and its attributes:
General information
| Iris plants data set | |||
|---|---|---|---|
| Type | Classification | Origin | Real world |
| Features | 4 | (Real / Integer / Nominal) | (4 / 0 / 0) |
| Instances | 150 | Classes | 3 |
| Missing values? | No | ||
Attribute description
| Attribute | Domain |
|---|---|
| SepalLength | [4.3, 7.9] |
| SepalWidth | [2.0, 4.4] |
| PetalLength | [1.0, 6.9] |
| PetalWidth | [0.1, 2.5] |
| Class | {Iris-setosa, Iris-versicolor, Iris-virginica} |
Additional information
This is perhaps the best known database to be found in the pattern recognition literature. 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.
In this section you can download some files related to the iris data set:
- The complete data set already formatted in KEEL format can be downloaded from
here
. - A copy of the data set already partitioned by means of a 10-folds cross validation procedure can be downloaded from here.
- A copy of the data set already partitioned by means of a 5-folds cross validation procedure can be downloaded from here.
- The header file associated to this data set can be downloaded from here
. - This is not a native data set from the KEEL project. It has been obtained from the UCI Machine Learning Repository. The original page where the data set can be found is: http://archive.ics.uci.edu/ml/datasets/Iris.
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