seckcoder
diff --git a/‎doc/datasets/covtype.rst
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+2-1Lines changed: 2 additions & 1 deletion b/‎doc/datasets/covtype.rst
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+2-1Lines changed: 2 additions & 1 deletion
diff --git a/‎doc/datasets/index.rst
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@@ -14,6 +14,7 @@ Some of the features are boolean indicators,
 while others are discrete or continuous measurements.
 
 ``sklearn.datasets.fetch_covtype`` will load the covertype dataset;
-it returns a ``Bunch`` object with the feature matrix in the ``data`` member
+it returns a dictionary-like object
+with the feature matrix in the ``data`` member
 and the target values in ``target``.
 The dataset will be downloaded from the web if necessary.
@@ -32,11 +32,11 @@ numpy array X and an array of length n_samples containing the targets y.
 
 The toy datasets as well as the 'real world' datasets and the datasets
 fetched from mldata.org have more sophisticated structure.
-These functions return a ``bunch`` (which is a dictionary that is
-accessible with the 'dict.key' syntax).
-All datasets have at least two keys, ``data``, containg an array of shape
-``n_samples x n_features`` (except for 20newsgroups) and ``target``, a numpy
-array of length ``n_features``, containing the targets.
+These functions return a dictionary-like object holding at least two items:
+an array of shape ``n_samples`` * `` n_features`` with key ``data``
+(except for 20newsgroups)
+and a NumPy array of length ``n_features``, containing the target values,
+with key ``target``.
 
 The datasets also contain a description in ``DESCR`` and some contain
 ``feature_names`` and ``target_names``.