Fixed small formatting changes

doc/glossary.rst

@@ -810,16 +810,17 @@ Class APIs and Estimator Types
         * :term:`predict` if :term:`inductive`
 
     density estimator
-        A :term:'unsupervised' :term:'estimator' estimating density of dataset inputs without 
-        labeled response
-        Most commonly used techniques are `Histogram <https://scikit-learn.org/stable/modules/density.html>`_, 
-        `Gaussian Mixtures <https://scikit-learn.org/stable/modules/generated/sklearn.mixture.GaussianMixture.html#sklearn.mixture.GaussianMixture>`_, 
-        and `kernel density estimate <https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KernelDensity.html#sklearn.neighbors.KernelDensity>`_
-        * Histogram- visually represent density of specific bins
-        * Gaussian Mixtures are discussed in `Clustering <https://scikit-learn.org/stable/modules/clustering.html#clustering>`_ 
-        * Kernel density estimate have multiple forms to represent density 
-          based on bandwidth 
-        It can also perform on multi-dimension graph
+        An :term:`unsupervised` estimation of input density without a labeled response.
+        Most commonly used techniques are `Histograms <https://scikit-learn.org/stable/modules/density.html#density-estimation-histograms>`_, 
+        `GaussianMixture`, 
+        and `KernelDensity` estimation.
+
+        * `Histograms <https://scikit-learn.org/stable/modules/density.html#density-estimation-histograms>`_
+          visually represents the density of specific bins.
+        * Gaussian Mixtures are discussed in `Clustering`. 
+        * Kernel density estimation has multiple forms to represent density based on bandwidth.
+
+        It can also be performed on a multi-dimensional graph.
 
     estimator
     estimators