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Results tagged with python
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user 92493
Python is a programming language commonly used for machine learning. Use this tag for any *on-topic* question that (a) involves `Python` either as a critical part of the question or expected answer, & (b) is not *just* about how to use `Python`.
10
votes
1
answer
15k
views
Why are all Lasso coefficients in model 0.0?
I'm using from sklearn.linear_model import Lasso in Python 2.7.6
I wrote a script that I've used for doing a Lasso regression for my Features (X) and my Targets (y) . …
- 1,502
13
votes
1
answer
75k
views
How to correctly compute mutual information (Python Example)? [closed]
def shannon_entropy(A, mode="auto", verbose=False):
"""
https://stackoverflow.com/questions/42683287/python-numpy-shannon-entropy-array
"""
A = np.asarray(A)
# Determine distribution …
- 1,502
2
votes
0
answers
2k
views
How does Principal Coordinate Analysis (PCoA) work, as compared to PCA? [duplicate]
Here's some Python 3 code I made to do PCA. …
- 1,502
8
votes
1
answer
13k
views
When should I use `scipy.stats.wilcoxon` instead of `scipy.stats.ranksums`? [duplicate]
I've been using http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.wilcoxon.html but then I realized that there is http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.ranksums …
- 1,502
5
votes
1
answer
2k
views
PyMC3; create simple Linear Regression model with real-world datasets
I thought the best way to understand this would be to code it myself using the datasets in scikit-learn (Python 3.5.1). …
- 1,502
6
votes
2
answers
4k
views
Optimize starting parameters for Bayesian Linear Regression?
I'm using PyMC3 in Python 3 and I'm not sure exactly how to optimize my starting parameters. …
- 1,502
0
votes
2
answers
854
views
Reversing "mean-centered" parameters in a multiple linear regression
I'm reading "Bayesian Analysis with Python" by Osvaldo Martin (great read btw) and in his hierarchical linear models section he often mean-centers the data and the reverses it. … The author implements it in Python 3.5 using a module that is up and coming called pymc3. Here is the code excerpt below:
alpha_tmp is the alpha when X is mean centered. …
- 1,502
2
votes
1
answer
166
views
How to structure this problem in a bayesian paradigm? (Updating the posterior?)
label=i)
legend_kws = {'bbox_to_anchor': (1, 0.5), 'edgecolor': 'black', 'facecolor': 'white', 'fontsize': 10, 'frameon': True, 'loc': 'center left'}
ax.legend(**legend_kws)
Versions:
Python …
- 1,502