Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 2 hours ago.
Improve this question
I have following algorithm I will implement in Python:
I'm not sure how to build it up and especially to deal with the minimum function. Can anyone help me?
I have self made the norm of the gradiant calculated out from matrix A and vector b by following:
r=b-A#x
r_new=np.inner(r,r)
np.sqrt(r_new)
But how do I deal with the minimum function and the setup. Can anyone help me?
Related
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 3 days ago.
Improve this question
I am trying to understand what is Brute Force approach in Python?
I have a Lennard-Jones potential equation and my interatomic distance value is unknown, so my professor told me to use the Brute Force approach.
I don't know how to do so, can you explain it to me with a little simple code example?
Thank you
Closed. This question needs details or clarity. It is not currently accepting answers.
Want to improve this question? Add details and clarify the problem by editing this post.
Closed 3 years ago.
Improve this question
Can anyone tell me what is the difference between the pearson correlation method and the normal corr() method? I expect it to be the same output, is that right?
no difference, if method='pearson'
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 3 years ago.
Improve this question
I am working on a FFT program, and I would like to get the frequency which has the largest amplitude or intensity in a sound. I checked out some codes on internet, but I couldn't find how to get the amplitude on a python program.
Check librosa.core.stft This gives magnitude of each frequency bin at given time. More details here:
https://librosa.github.io/librosa/generated/librosa.core.stft.html?highlight=stft#librosa.core.stft
Closed. This question needs details or clarity. It is not currently accepting answers.
Want to improve this question? Add details and clarify the problem by editing this post.
Closed 5 years ago.
Improve this question
I have a question about the Levenberg-Marquardt optimize method in Python:
Generally, the Lavenberg Maquardt is used for deterministic systems. Can I use it for stochastic model to estimate unknown parameters (inputs of my model).
Thanks
The requirement for the Levenberg Marquard algorithm is that you need to be able to calculate the jacoboan (derivative with respect to your parameter).
If this is the case for your problem then yes. I guess that it is not.
Perhaps the simplex algorithm is what you are looking for.
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 6 years ago.
Improve this question
Would someone please kindly explain what sklearn.tree.DecisionTreeClassifier.predict(X) and .predict_log_proba(X) and .predict_proba(X) are?
Thanks a lot in advance.
Here's the link to sklearn's library:
In short words (and this applies to all sklearn models):
predict_proba(x) = P(y|x) (probability of each label as a vector)
predict_log_proba(x) = log P(y|x) (logarithm of the above)
predict(x) = arg max_y P(y|x) (the most probable label using the above)