用于实现决策树的语言
实现决策树的最佳编程语言是什么？实现的结果仅供个人使用，因此无需考虑发布能力等。
我听说Octave是一个不错的选择，有人可以解释为什么建议使用基于矩阵的语言来实现决策树吗？
What would be a good choice of programming language in which to implement a decision tree? The results of the implementation will be for personal use only, so no need to consider ability to publish etc.
I have heard that Octave is a good option, can anyone explain why a matrix based language is recommended for implementing decision trees?
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我使用了标准机器学习来实现决策树，并将编译器从特定于领域的语言编写为决策树。我还将类似的决策树编译成 C 代码。
这实际上取决于您想用决策树做什么。如果您正在尝试做一些复杂的事情或者您正在尝试使决策树特别易于阅读和编写，我建议您创建特定于域的语言或将特定于域的运算符嵌入 Haskell 或标准机器学习。如果你只是想开始，你可以从 ML 开始（对于初学者来说比 Haskell 更容易），这为以后保留了一些选择。
总的来说，ML 和 Haskell 都非常擅长表示和操作各种树。
我无法解释为什么有人会推荐基于矩阵的决策树语言。
I have used Standard ML both to implement decision trees and to write a compiler from a domain-specific language into decision trees. I've also compiled similar decision trees into C code.
It really depends what you want to do with decision trees. If you are trying to do something sophisticated or you are trying to make the decision trees especially easy to read and write, I would suggest either creating a domain-specific language or embedding domain-specific operators into Haskell or Standard ML. If you just want to get going, you could start with ML (easier than Haskell for a beginner) and that preserves some options for later.
In general, ML and Haskell are both very good at representing and manipulating trees of all kinds.
I can't explain why someone would recommend a matrix-based language for decision trees.
我非常确定第一个决策树是用 LISP 编写的。
还有很多这样的算法仍然是用 LISP 编写的。
如果您决定选择 LISP，您可以找到许多文档。
对于此目的，Scheme 也是一种很好的语言，并且它比 LISP 更简单/更小。
而且两种语言的学习曲线都很快。
恕我直言
I am pretty sure that the first decision tree was written in LISP.
Still many such algorithm is still written in LISP.
You can find many documentation if you decide to choose LISP.
Scheme is also a good language for that purpose and it is simpler/smaller than LISP.
Also the learning curve is fast in both languages.
IMHO