Opencv 如何解释haartraining结果？

我的haartraining程序目前正在我的计算机上运行。 我使用了1700个阳性样本和1300个阴性样本。我已运行以下命令行：

opencv_traincascade -data data -vec cars.vec -bg bg.txt -numStages 10 -nsplits 2 -minhitrate 0.999 -maxfalsealarm 0.5 -numPos 1600 -numNeg 1371 -w 48 -h 24

目前，报告如下：

===== TRAINING 0-stage =====
<BEGIN
POS count : consumed   1600 : 1600
NEG count : acceptanceRatio    1371 : 1
Precalculation time: 16
+----+---------+---------+
|  N |    HR   |    FA   |
+----+---------+---------+
|   1|        1|        1|
+----+---------+---------+
|   2|        1|        1|
+----+---------+---------+
|   3|        1|        1|
+----+---------+---------+
|   4|  0.99875| 0.587163|
+----+---------+---------+
|   5|  0.99875| 0.587163|
+----+---------+---------+
|   6| 0.995625| 0.305616|
+----+---------+---------+
END>
Training until now has taken 0 days 0 hours 21 minutes 19 seconds.

===== TRAINING 1-stage =====
<BEGIN
POS count : consumed   1600 : 1607
NEG count : acceptanceRatio    1371 : 0.338853
Precalculation time: 18
+----+---------+---------+
|  N |    HR   |    FA   |
+----+---------+---------+
|   1|        1|        1|
+----+---------+---------+
|   2|        1|        1|
+----+---------+---------+
|   3|        1|        1|
+----+---------+---------+
|   4|        1|        1|
+----+---------+---------+
|   5| 0.998125| 0.786287|
+----+---------+---------+
|   6|   0.9975| 0.673961|
+----+---------+---------+
|   7| 0.995625| 0.560175|
+----+---------+---------+
|   8|   0.9975| 0.531729|
+----+---------+---------+
|   9| 0.995625| 0.406273|
+----+---------+---------+
END>
Training until now has taken 0 days 0 hours -19 minutes -57 seconds.

===== TRAINING 2-stage =====
<BEGIN
POS count : consumed   1600 : 1614
NEG count : acceptanceRatio    1371 : 0.136649
Precalculation time: 17
+----+---------+---------+
|  N |    HR   |    FA   |
+----+---------+---------+
|   1|        1|        1|
+----+---------+---------+
|   2|        1|        1|
+----+---------+---------+
|   3|        1|        1|
+----+---------+---------+
|   4| 0.998125| 0.856309|
+----+---------+---------+
|   5| 0.999375| 0.875274|
+----+---------+---------+
|   6| 0.996875| 0.633115|
+----+---------+---------+
|   7| 0.995625| 0.546317|
+----+---------+---------+
|   8| 0.995625| 0.501094|
+----+---------+---------+
|   9|  0.99625| 0.524435|
+----+---------+---------+
|  10| 0.995625| 0.404814|
+----+---------+---------+
END>
Training until now has taken 0 days 0 hours 14 minutes 52 seconds.

====培训0级=====
到目前为止，训练时间为0天0小时21分19秒。
====培训一阶段=====
到目前为止，训练需要0天0小时19分57秒。
====培训2阶段=====
到目前为止，训练时间为0天0小时14分52秒。

因此，在第二阶段训练结束时，我仍然看到0.4的错误警报率。在一些教程之后，我选择了一个10级级联。我在某个地方读到过一个好的分类器应该是10^-5 FA左右，所以我猜在第2阶段结束时为0.404，很难在第10阶段结束时达到10^-5 FA的速率。我说得对吗？我应该停止并改进我的阴性和阳性样本吗

[编辑]我想我混淆了每个阶段的固定资产比率和一般接受率

另一个问题浮现在我的脑海中：舞台数量的影响是什么？性能与速度