Add info about using PCA pairs plot and PCA beta coefficients to Usage docs

[asromriell]

Let's try this again...

[nsh87]

@asromriell: perfect! there's a little icon next to your latest commit - it's an orange circle right now. if you click on it, you'll see Travis CI trying to build the package. if there are any errors in the package or when building the docs (i.e. from your new usage.rst file), it will become a red X. Green checkmark is obviously good...

[nsh87]

@asromriell: fyi, i've taken the logistic regression function you made out for now. scikit-learn's confusion matrix is different than we're used to, so the true positives/true negatives are somewhat switched from how you were getting them. i'm going to implement all the stuff for the project first, then add stuff like this back in b/c i don't have a ton of time left to unit test and check things. i think the best way to include that logistic regression stuff is to output that stuff that you put at the end if someone passes a logistic regression model to summary().

[asromriell]

Sounds fine. I wasn't too impressed with what I did with the logistic
regression anyway. And yeah, seaborn never worked for me. And probably will
give other ppl trouble too
On Dec 8, 2015 3:39 AM, "Nikhil Haas" notifications@github.com wrote:

@asromriell https://github.com/asromriell: fyi, i've taken the logistic
regression function you made out for now. scinkit-learn's confusion matrix
is different than we're used to, so the true positives/true negatives are
somewhat switched from how you were getting them. i'm going to implement
all the stuff for the project first, then add stuff like this back in. i
think the best way to include that logistic regression stuff is to output
that stuff that you put at the end if someone passes a logistic regression
model to summary().

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