Comments (2)
Both achieve the same goal, although I can imagine sum_P
may be slightly different from 2n in practice because of numerical issues.
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Well. Sure, they are different. They have different values. But although I have to admit that this is not really a satisfactory answer, it answers my question at least implicitly: There are some magic factors and guesses involved, and the implementation may have some degrees of freedom (only justified by how well they work in one or the other case).
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Related Issues (20)
- Usage of random generator(s) in the source HOT 2
- How can i visualize the image data like this? HOT 1
- bhtsne.py:135: ComplexWarning: Casting complex values to real discards the imaginary part HOT 1
- Butterfly effect HOT 3
- Can not use the python wrapper in Windows
- transposition based on input method HOT 3
- Why is the exact algorithm 10 times faster? HOT 8
- Dimension problem HOT 3
- Can't compile the .exe with visual studio 9.0 HOT 9
- Pytorch version? HOT 4
- python wrapper - Cost for each sample
- Performance difference to the old version HOT 1
- C API HOT 3
- Bhtsne for large datasets HOT 1
- Performance difference Windows/Ubuntu HOT 2
- t-SNE for Java/Scala/Kotlin/Clojure
- Is there a rule of thumb for the lower bound on the perplexity?
- Why use zeroMean in gradient update?
- Finding P and Q matrices
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