High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
您好,最近在看FFM模型实现部分有一点困惑,从预测代码实现中看,feature_id 应该是连续累加的,也就是说不同 field 之间的feature index 应该是连续增加的,像FM一样。
Hi,I have a problem about FFM calc score。what I got from the code is that 'feature_id' should be continuous, like what we did in FM.
但是在给出的 demo 数据却发现feature index 并不是累加的。发现 featureid 之间的数据存在大小颠倒和相等的列。如下:
But the test data is not what I expected.So am I missing something or the test data was just randomly generated?
thanks for all.
请问是我对代码理解有问题?还是 demo 数据是随机生成?
您好,最近在看FFM模型实现部分有一点困惑,从预测代码实现中看,feature_id 应该是连续累加的,也就是说不同 field 之间的feature index 应该是连续增加的,像FM一样。 Hi,I have a problem about FFM calc score。what I got from the code is that 'feature_id' should be continuous, like what we did in FM.
![image](https://user-images.githubusercontent.com/9072860/60063880-0edbfa80-9731-11e9-8804-55e608193327.png)
但是在给出的 demo 数据却发现feature index 并不是累加的。发现 featureid 之间的数据存在大小颠倒和相等的列。如下: But the test data is not what I expected.So am I missing something or the test data was just randomly generated? thanks for all.
请问是我对代码理解有问题?还是 demo 数据是随机生成?