Narrowing the Gap: Random Forests In Theory and In Practice
Narrowing the Gap: Random Forests In Theory and In Practice
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发表时间：
2013-10
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通讯作者：
Misha Denil;David Matheson;Nando de Freitas
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作者：
Misha Denil;David Matheson;Nando de Freitas
尽管有广泛的兴趣和实际应用，随机森林的理论性质仍然没有得到很好的理解。在本文中，我们有助于这种理解在两个方面。我们提出了一个新的理论上易于处理的随机回归森林的变种，并证明我们的算法是一致的。我们还提供了一个实证评估，比较我们的算法和其他理论上易于处理的随机森林模型的随机森林算法在实践中使用。我们的实验提供了洞察不同的简化，理论家已经获得易于处理的模型进行分析的相对重要性。
Despite widespread interest and practical use, the theoretical properties of random forests are still not well understood. In this paper we contribute to this understanding in two ways. We present a new theoretically tractable variant of random regression forests and prove that our algorithm is consistent. We also provide an empirical evaluation, comparing our algorithm and other theoretically tractable random forest models to the random forest algorithm used in practice. Our experiments provide insight into the relative importance of different simplifications that theoreticians have made to obtain tractable models for analysis.