December 2018
Intermediate to advanced
274 pages
7h 46m
English
Content preview from Machine Learning for Mobile
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Random forest
We have already seen what a decision tree is. Having understood decision trees, let's take a look at random forests. A random forest combines many decision trees into a single model. Individually, predictions made by decision trees (or humans) may not be accurate, but combined together, the predictions will be closer to the mark, on average.
The following diagram shows us a random forest, where there are multiple trees and each is making a prediction:
Random forest is a combination of many decision trees and, hence, there is a greater probability of having many views from all trees in the forest to arrive at the final desired outcome/prediction. ...
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I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.