Symmetry of Best Fit Straight Line on Inverting Axes
I have a set of data that I have created a scatter plot from. On top of this I overlay the best fit straight line. Everything was fine until I realised that because of the nature of the data, it made more conceptual sense if the y-axis data was plotted on the x-axis. So I inverted the axes
Symmetry of straight line fit on inverting axes
I have a set of data that I have created a scatter plot from
On top of this I overlay the best fit straight line
Everything was fine until I realised that because of the nature of the data, it made more conceptual sense if the y-axis data was plotted on the x-axis. So I inverted them
Is there a way to calculate Wasserstein Distance / EMD Distance of two continuous empirical distributions?
I’ve looked at various different websites that seem to have implementations of Wasserstein distance in the discrete case, however, none of them have the continuous case?
How to prevent line wrapping in console log?
I have the following code:
Why is using the “distance.cosine” function from SciPy faster than directly executing its Python code?
I am executing the below two code snippets to calculate the cosine similarity of two vectors where the vectors are the same for both executions and the code for the second one is mainly the code SciPy is running (see scipy cosine implementation).
Why using the “distance.cosine” function from SciPy is running faster than directly executing its Python code?
I am executing below two code snippets to calculate the cosine similarity of two vectors where the vectors are the same for both executions and the code for the second one is mainly the code SciPy is running (see scipy cosine implementation).