如何理解Spark MLlib的libsvm的格式类型? [英] How to understand the format type of libsvm of Spark MLlib?
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问题描述
我是学习 Spark MLlib 的新手.当我阅读二项式逻辑回归的例子时，我不明白libsvm"的格式类型.(二项逻辑回归)
I am new for learning Spark MLlib. When I was reading about the example of Binomial logistic regression, I don't understand the format type of "libsvm". (Binomial logistic regression)
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能帮我了解一下 Spark MLlib 的 libsvm 的格式类型吗?谢谢！
Can you help me to understand the format type of libsvm of Spark MLlib? Thanks!
推荐答案
LibSVM 格式非常简单.第一行包含类别标签，在本例中为 0 或 1.接下来是特征，这里每个特征有两个值；第一个是特征索引(即它是哪个特征)，第二个是实际值.
The LibSVM format is quite simple. The first row contains the class label, in this case 0 or 1. Following that are the features, here there are two values for each one; the first one is the feature index (i.e. which feature it is) and the second one is the actual value.
特征索引从 1 开始(没有索引 0)并且按升序排列.一行中不存在的索引为 0.
The feature indices starts from 1 (there is no index 0) and are in ascending order. The indices not present on a row are 0.
总结起来，每一行都是这样的；
In summary, each row looks like this;
<label> <index1>:<value1> <index2>:<value2> ... <indexN>:<valueN>
<小时>
当数据稀疏且包含大量零时使用这种格式是有利的.不保存所有 0 值，这将使文件更小且更易于阅读.
This format is advantageous to use when the data is sparse and contain lots of zeroes. All 0 values are not saved which will make the files both smaller and easier to read.
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