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