For the first problem, it’s about the precision. In our previous grading
script. We use 1e-5 to compare the difference from your answer to ours. But
for Gaussian Kernel distance, the value of it is too small that it’s far
less than 1e-5.
However, if we use a very high precision. It will influence the grading of f1
score and IG function. Finally, we decided to use 1e-10. Although some
Gaussian Kernel distance is still bellow this value. I would say it’s kind
of trade off. Any better idea?
可以先不用看第二段
故事是這樣 有個function要回傳 -exp(-0.5*<a-b, a-b>)
其中exp()是自然指數 <a, b>指的是兩向量a,b內積
然後我就亂戳傳exp(-0.5*<a-b, a-b>)結果Online Judge也給過
我就寄信去問結果助教回這個
你他媽連正的值先去掉都不會嗎
然後精度不會處理那還要出這個function自討苦吃
這種爛人一個月學校付他1200美金
可撥學店幹x