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//! Decision trees suffer from high variance and often does not deliver best prediction accuracy when compared to other supervised learning approaches, such as linear and logistic regression.
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//! Hence some techniques such as [Random Forests](../ensemble/index.html) use more than one decision tree to improve performance of the algorithm.
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//!
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//! smartcore uses [CART](https://en.wikipedia.org/wiki/Predictive_analytics#Classification_and_regression_trees_.28CART.29) learning technique to build both classification and regression trees.
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//! `smartcore` uses [CART](https://en.wikipedia.org/wiki/Predictive_analytics#Classification_and_regression_trees_.28CART.29) learning technique to build both classification and regression trees.
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//!
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//! ## References:
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//!
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