Updating docs

Author: perimosocordiae

doc/metric_learn.mlkr.rst

@@ -0,0 +1,27 @@
+Metric Learning for Kernel Regression (MLKR)
+============================================
+
+.. automodule:: metric_learn.mlkr
+    :members:
+    :undoc-members:
+    :inherited-members:
+    :show-inheritance:
+
+Example Code
+------------
+
+::
+
+    from metric_learn import MLKR
+    from sklearn.datasets import load_iris
+
+    iris_data = load_iris()
+    X = iris_data['data']
+    Y = iris_data['target']
+
+    mlkr = MLKR()
+    mlkr.fit(X, Y)
+
+References
+----------
+`Information-theoretic Metric Learning <http://machinelearning.wustl.edu/mlpapers/paper_files/icml2007_DavisKJSD07.pdf>`_ Jason V. Davis, et al.

doc/metric_learn.mmc.rst

@@ -0,0 +1,27 @@
+Mahalanobis Metric Learning for Clustering (MMC)
+================================================
+
+.. automodule:: metric_learn.mmc
+    :members:
+    :undoc-members:
+    :inherited-members:
+    :show-inheritance:
+
+Example Code
+------------
+
+::
+
+    from metric_learn import MMC_Supervised
+    from sklearn.datasets import load_iris
+
+    iris_data = load_iris()
+    X = iris_data['data']
+    Y = iris_data['target']
+
+    mmc = MMC_Supervised(num_constraints=200)
+    mmc.fit(X, Y)
+
+References
+----------
+`Distance metric learning with application to clustering with side-information <http://papers.nips.cc/paper/2164-distance-metric-learning-with-application-to-clustering-with-side-information.pdf>`_ Xing, Jordan, Russell, Ng.

doc/metric_learn.rst

@@ -11,6 +11,8 @@ Submodules
    metric_learn.lfda
    metric_learn.lmnn
    metric_learn.lsml
+   metric_learn.mlkr
+   metric_learn.mmc
    metric_learn.nca
    metric_learn.rca
    metric_learn.sdml

metric_learn/mlkr.py

@@ -72,7 +72,7 @@ def fit(self, X, y):
       """
       Fit MLKR model
 
-      Parameters:
+      Parameters
       ----------
       X : (n x d) array of samples
       y : (n) data labels