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.. _covtype_dataset:
Forest covertypes
-----------------
The samples in this dataset correspond to 30×30m patches of forest in the US,
collected for the task of predicting each patch's cover type,
i.e. the dominant species of tree.
There are seven covertypes, making this a multiclass classification problem.
Each sample has 54 features, described on the
`dataset's homepage <https://archive.ics.uci.edu/ml/datasets/Covertype>`__.
Some of the features are boolean indicators,
while others are discrete or continuous measurements.
**Data Set Characteristics:**
================= ============
Classes 7
Samples total 581012
Dimensionality 54
Features int
================= ============
:func:`sklearn.datasets.fetch_covtype` will load the covertype dataset;
it returns a dictionary-like 'Bunch' object
with the feature matrix in the ``data`` member
and the target values in ``target``. If optional argument 'as_frame' is
set to 'True', it will return ``data`` and ``target`` as pandas
data frame, and there will be an additional member ``frame`` as well.
The dataset will be downloaded from the web if necessary.
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