问题描述
我有一个带有文本描述和分类级别(即levelA和levelB)的输入文件.我想编写一个可测量精度,召回率和准确性的SVM分类器.我看了 scikit 和 LIBSVM ,但我想逐步了解更多信息.
I have a input file with text description and classified level (i.e.levelA and levelB). I want to write a SVM classifier that measure precision, recall and accuracy. I looked at scikitand LIBSVM but I want to know more step by step.
任何示例代码或基本教程都将非常不错.感谢您提前提出任何建议.
Any sample code or basic tutorial would be really nice. Thanks for any suggestion in advance.
推荐答案
这些性能指标很容易从预测标签和真实标签中获取,作为后期处理步骤:
These performance measures are easy to obtain from the predicted labels and true labels, as a post-processing step:
- 精度= TP/(TP + FP)
- 召回= TP/(TP + FN)
- 精度=(TP + TN)/(TP + TN + FP + FN)
其中TP,FP,TN和FN分别为真阳性,假阳性,真阴性和假阴性的数量.
With TP, FP, TN, FN being number of true positives, false positives, true negatives and false negatives, respectively.
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