Differences

This shows you the differences between two versions of the page.

--- courses:mapreduce-tutorial:step-15 [2012/01/25 15:46]
straka vytvořeno
+++ courses:mapreduce-tutorial:step-15 [2012/01/29 16:40] (current)
straka
@@ Line 1: / Line 1: @@
-====== MapReduce Tutorial :  ======
+====== MapReduce Tutorial : K-means clustering ======
+Implement the [[http://en.wikipedia.org/wiki/K-means_clustering#Standard_algorithm|K-means clustering algorithm]]. You can use the following data:
+^ Path ^ Number of points ^ Number of dimensions ^ Number of clusters ^
+| ''/net/projects/hadoop/examples/inputs/points-small'' | 10000 | 50 | 50 |
+| ''/net/projects/hadoop/examples/inputs/points-medium'' | 100000 | 100 | 100 |
+| ''/net/projects/hadoop/examples/inputs/points-large'' | 500000 | 200 | 200 |
+When dealing with iterative algorithms, each iteration is usually implemented as one Hadoop job. The Hadoop ''input_path'' should contain the input data and each mapper should also read the current clusters. The reducers are used to aggregate the data and output new cluster centers. A controlling script should take care of executing Hadoop jobs and stopping the iteration when the algorithm converges.
+----
+<html>
+<table style="width:100%">
+<tr>
+<td style="text-align:left; width: 33%; "></html>[[step-14|Step 14]]: N-gram language model.<html></td>
+<td style="text-align:center; width: 33%; "></html>[[.|Overview]]<html></td>
+<td style="text-align:right; width: 33%; "></html><html></td>
+</tr>
+</table>
+</html>

Institute of Formal and Applied Linguistics Wiki