随机森林在opencv python(cv2)中不起作用 [英] Random Forest not working in opencv python (cv2)

问题描述

我似乎无法正确地传递参数来从python的opencv中训练随机森林分类器.

I can't seem to correctly pass in the parameters to train a Random Forest classifier in opencv from python.

我用C ++编写了一个可以正常工作的实现，但是在python中却没有得到相同的结果.

I wrote an implementation in C++ which worked correctly, but do not get the same results in python.

我在这里找到了一些示例代码:

I found some sample code here: http://fossies.org/linux/misc/opencv-2.4.7.tar.gz:a/opencv-2.4.7/samples/python2/letter_recog.py

似乎表明您应该在字典中传递参数.这是我正在使用的代码:

which seems to indicate that you should pass in the parameters in a dict. Here is the code I am using:

rtree_params = dict(max_depth=11, min_sample_count=5, use_surrogates=False, max_categories=15, calc_var_importance=False, n_active_vars=0, max_num_of_trees_in_the_forest=1000, termcrit_type=cv2.TERM_CRITERIA_MAX_ITER)
classifier = cv2.RTrees()
classifier.train(train_data, cv2.CV_ROW_SAMPLE, label_data, params=rtree_params);

我可以告诉您分类器正在正确地训练，但是它不如我在C ++中使用相同参数训练的分类器那么准确.我相当确定这些参数已经得到确认，因为在调整值时会得到不同的结果.

I can tell that the classifier is getting trained correctly, but it is not nearly as accurate as the one I trained with the same parameters in C++. I'm fairly certain that the parameters are getting acknowledged, because I get different results when I tweak the values.

我确实注意到，当我将分类器输出到文件时，它只有一棵树.我很确定这是问题所在.我看了一下openCV的实现:

I did notice that when I output the classifier to a file, it only has one tree. I'm pretty sure this is the problem. I looked at the openCV implementation:

http://www.code.opencv.org/svn/gsoc2012/denoising/trunk/opencv-2.4.2/modules/ml/src/rtrees.cpp

给出我的参数，它应该输出一个有1000棵树的森林.我尝试将max_num_of_trees_in_the_forest参数设置为各种疯狂的值，但这并没有改变OpenCV的行为.

Given my parameters, it should output a forest with 1000 trees. I tried setting the max_num_of_trees_in_the_forest arguments to all sorts of crazy values, and it didn't change OpenCV's behaviour.

有想法吗?

推荐答案

不确定是否会有所帮助，但我相信:

Not sure if this will help much, but I believe:

n_active_vars=0

应该是

nactive_vars=0

此外，您可能希望尝试使用term_crit参数. 例如，尝试添加:

Also, you may wish to try experimenting with the term_crit parameter. For example, try adding:

term_crit=(cv2.TERM_CRITERIA_MAX_ITER,1000,1)

进入字典.

我相信这将为在森林中添加1000棵树时终止设置标准.

I believe this will set the criteria to terminate when 1000 trees are added into the forest.

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