Cross Entropy
pandeykartikey.github.io
Cross Entropy
1–10 of 13 posts
Re: Cross Entropy
#2Why link to the disqus thread?
Re: Cross Entropy
#3What I always wondered about is that this generally assumes that classes are assigned with an equal (human level) error probability. While this is certainly the case in heavily curated example dataset, many real world scenarios only consist of a considerably labeled positive set while the negative set is often drawn randomly from the background. Is there anything on how this can be taken into account (Besides weighting, obviously)?
Re: Cross Entropy
#4What I always wondered about is that this generally assumes that classes are assigned with an equal (human level) error probability. While this is certainly the case in heavily curated example dataset, many real world scenarios only consist of a considerably labeled positive set while the negative set is often drawn randomly from the background. Is there anything on how this can be taken into account (Besides weighti…
I too have been thinking about this problem, but I have yet to come across a viable solution.
Re: Cross Entropy
#5Aside: I'm always surprised how few people notice that e.g. "cos" is rendered differently to "\cos" in TeX; for a discipline largely characterised by attention to detail, almost no programmers seem to notice.
Re: Cross Entropy
#6Aside: I'm always surprised how few people notice that e.g. "cos" is rendered differently to "\cos" in TeX; for a discipline largely characterised by attention to detail, almost no programmers seem to notice.
I'm always surprised when people use ^T for transpose. Use ^\top, people.
Re: Cross Entropy
#7Nice read! Looking forward to more blogs.
Re: Cross Entropy
#8"Cross-entropy is defined as the difference between the following two probability distributions"
Huh? No this is a mathematically imprecise statement (and not correct either). Most explanations use references to information theory, where a perfect knowledge of the desired probability distribution leads to a perfect allocation of bits in a binary encoding. The entropy is the expected number of bits when this allocation is done using the incorrect distribution, and obviously the goal is to minimize this, hence why it is suitable for use as a loss function.
Re: Cross Entropy
#9Please do not put "Show HN" on blog posts. This is in the rules: https://news.ycombinator.com/showhn.html.
Re: Cross Entropy
#10"Cross-entropy is defined as the difference between the following two probability distributions" Huh? No this is a mathematically imprecise statement (and not correct either). Most explanations use references to information theory, where a perfect knowledge of the desired probability distribution leads to a perfect allocation of bits in a binary encoding. The entropy is the expected number of bits when this allocatio…
> The entropy is the expected number of bits when this allocation is done using the incorrect distribution
Is there any source that would derive and/or explain this more in-depth? I've been trying to develop an intuition for this, but haven't come across a good explanation.