Spark-Sequoia-Forest-Random-Forest-of-Humongous-Trees-Sung-Chung.pdf
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Sequoia Forest
A Scalable Random Forest
Implementation on Spark
Sung Hwan Chung, Alpine Data Labs
Random Forest Overview
● It’s a technique to reduce the variance of
single decision tree predictions by averaging
the predictions of many decorrelated trees.
● The decorrelation of many decision trees is
achieved through Bagging and/or randomly
selecting features per tree node.
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