Numerai is synthesizing machine intelligence to command the capital of an American hedge fund. Here’s how.

Combining Intelligence In the late 90s and early 2000s, new algorithms such as AdaBoost and Random Forests made breakthroughs in machine learning. The principle behind each of these algorithms was very simple: build many decision tree models that each learn something different, and then average them all together to create an ensemble model.

These algorithms worked incredibly well. They were easy to understand, and computationally efficient. Decision tree ensembles were so effective that in many cases they would outperform complicated neural networks on machine learning benchmarks. To compete, neural network researchers needed to find a way to harness their power: the power of combining many models.

Read more: Super Intelligence for The Stock Market – Medium

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Published by Mike Rawson

Mike Rawson has recently re-awoken a long-standing interest in robots and our automated future. He lives in London with a single android - a temperamental vacuum cleaner - but is looking forward to getting more cyborgs soon.

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Super Intelligence for The Stock Market – Medium

by Mike Rawson time to read: 1 min
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