Uploaded Test files

venv/Lib/site-packages/sklearn/datasets/descr/iris.rst

@@ -0,0 +1,63 @@
+.. _iris_dataset:
+
+Iris plants dataset
+--------------------
+
+**Data Set Characteristics:**
+
+    :Number of Instances: 150 (50 in each of three classes)
+    :Number of Attributes: 4 numeric, predictive attributes and the class
+    :Attribute Information:
+        - sepal length in cm
+        - sepal width in cm
+        - petal length in cm
+        - petal width in cm
+        - class:
+                - Iris-Setosa
+                - Iris-Versicolour
+                - Iris-Virginica
+                
+    :Summary Statistics:
+
+    ============== ==== ==== ======= ===== ====================
+                    Min  Max   Mean    SD   Class Correlation
+    ============== ==== ==== ======= ===== ====================
+    sepal length:   4.3  7.9   5.84   0.83    0.7826
+    sepal width:    2.0  4.4   3.05   0.43   -0.4194
+    petal length:   1.0  6.9   3.76   1.76    0.9490  (high!)
+    petal width:    0.1  2.5   1.20   0.76    0.9565  (high!)
+    ============== ==== ==== ======= ===== ====================
+
+    :Missing Attribute Values: None
+    :Class Distribution: 33.3% for each of 3 classes.
+    :Creator: R.A. Fisher
+    :Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov)
+    :Date: July, 1988
+
+The famous Iris database, first used by Sir R.A. Fisher. The dataset is taken
+from Fisher's paper. Note that it's the same as in R, but not as in the UCI
+Machine Learning Repository, which has two wrong data points.
+
+This 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.
+
+.. topic:: References
+
+   - Fisher, R.A. "The use of multiple measurements in taxonomic problems"
+     Annual Eugenics, 7, Part II, 179-188 (1936); also in "Contributions to
+     Mathematical Statistics" (John Wiley, NY, 1950).
+   - Duda, R.O., & Hart, P.E. (1973) Pattern Classification and Scene Analysis.
+     (Q327.D83) John Wiley & Sons.  ISBN 0-471-22361-1.  See page 218.
+   - Dasarathy, B.V. (1980) "Nosing Around the Neighborhood: A New System
+     Structure and Classification Rule for Recognition in Partially Exposed
+     Environments".  IEEE Transactions on Pattern Analysis and Machine
+     Intelligence, Vol. PAMI-2, No. 1, 67-71.
+   - Gates, G.W. (1972) "The Reduced Nearest Neighbor Rule".  IEEE Transactions
+     on Information Theory, May 1972, 431-433.
+   - See also: 1988 MLC Proceedings, 54-64.  Cheeseman et al"s AUTOCLASS II
+     conceptual clustering system finds 3 classes in the data.
+   - Many, many more ...