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| <div class="block">Partial-data mapreduce implementation of Random Decision Forests</div> |
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| <div class="block"><h2>Partial-data mapreduce implementation of Random Decision Forests</h2> |
| |
| <p>The builder splits the data, using a FileInputSplit, among the mappers. |
| Building the forest and estimating the oob error takes two job steps.</p> |
| |
| <p>In the first step, each mapper is responsible for growing a number of trees with its partition's, |
| loading the data instances in its <code>map()</code> function, then building the trees in the <code>close()</code> method. It |
| uses the reference implementation's code to build each tree and estimate the oob error.</p> |
| |
| <p>The second step is needed when estimating the oob error. Each mapper loads all the trees that does not |
| belong to its own partition (were not built using the partition's data) and uses them to classify the |
| partition's data instances. The data instances are loaded in the <code>map()</code> method and the classification |
| is performed in the <code>close()</code> method.</p></div> |
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