adding isodata algorithm

Author: abranhe

docs/dbscan.md

@@ -90,7 +90,7 @@ DBSCAN visits each point of the database, possibly multiple times (e.g., as cand
 
 > DBSCAN can find non-linearly separable clusters. This dataset cannot be adequately clustered with k-means or Gaussian Mixture EM clustering
 
-## Implementations
+## Implementation
 
 | | Language | Link |
 |:-: | :-: | :-: |

docs/isodata.md

@@ -4,4 +4,10 @@ title: Isodata
 sidebar_label: Isodata
 ---
 
-[Open a pull request](https://github.com/AllAlgorithms/algorithms/tree/master/docs/isodata.md) to add the content for this algorithm.
+The Iterative Self-Organizing Data Analysis Technique (**ISODATA**) method used a set of rule-of-thumb procedures that have 
+incorporated into an iterative classification algorithm. Many of the steps used in the algorithm are based on the experience obtained through experimentation. The ISODATA algorithm is a modification of the [k-means clustering algorithm](k-means) (overcomes the disadvantages of k-means). This algorithm includes the merging of clusters if their separation distance in multispectral feature space is less than a user-specified value and the rules for splitting a single cluster into two clusters. This method makes a large number of passes through the dataset until specified results are obtained.
+
+
+## Helpful Links
+
+- [Wikipedia](https://en.wikipedia.org/wiki/Multispectral_pattern_recognition#ISODATA_method)