我的记录有多种不同类型的 mu洗室。 这些物质应归类为毒性和毒性。 分类必须使用K-nearest-neighbors(1)和J48。
这两种算法的精确度分别为99.88%。 对我来说,是错觉反应率。 J48的这一比例为0.3%,KNN为0%。 因此,我要说,有线电视新闻网更适合选定的问题。
然而,我知道为什么要回答。 是否有一个一般性答案,为什么有线电视新闻网的某些记录是不是J48的。
第二点是,我应当使用10倍的交叉验证。 这是什么?
预 收
我的记录有多种不同类型的 mu洗室。 这些物质应归类为毒性和毒性。 分类必须使用K-nearest-neighbors(1)和J48。
这两种算法的精确度分别为99.88%。 对我来说,是错觉反应率。 J48的这一比例为0.3%,KNN为0%。 因此,我要说,有线电视新闻网更适合选定的问题。
然而,我知道为什么要回答。 是否有一个一般性答案,为什么有线电视新闻网的某些记录是不是J48的。
第二点是,我应当使用10倍的交叉验证。 这是什么?
预 收
是否有一个一般性答案,为什么有线电视新闻网的某些记录是不是J48的。
页: 1 这在很大程度上取决于数据集、算法的两种环境以及你重新进行评价的方式(你确实使用单独的培训和测试套,是你?)
10倍的交叉验证意味着:你将数据集分成10个同等规模的“文件夹”,然后将数据集分成10个。
and take the average accuracy. See Wikipedia or any book on machine learning.
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