Re: [ojAlgo-user] Logistic Regression with Standard Errors

[Anders P. <an...@op...>]

That’s not ojAlgo code…

No, ojAlgo currently does not have BFGS and such.


> On 27 Sep 2018, at 21:40, Shantanu Lodh via ojAlgo-user <oja...@li...> wrote:
> 
> What I've tried so far is here: https://www.pastiebin.com/5bad3003800a4
> 
> This takes 4.5 secs to train a 4150 sample dataset with 2 regressors + 1 intercept, Python::statsmodels takes c.0.5 secs for the same. 
> 
> I've not done rigorous profiling but suspect the delay is due to calculating and inverting Hessians. 
> 
> Are there any quasi-Newton optimizations available on oj such as DFP, L-BFGS etc? Sorry if I've missed it already since I've just started looking at it. Thanks, Shan 
> From: Anders Peterson <an...@op...>
> Sent: Thursday, September 27, 2018 6:58 PM
> To: Shantanu Lodh
> Cc: oja...@li...
> Subject: Re: [ojAlgo-user] Logistic Regression with Standard Errors
>  
> There is no specific code for logistic regression in ojAlgo.
> 
> What did you try, and why is it slow?
> 
> 
> > On 27 Sep 2018, at 19:44, Shantanu Lodh via ojAlgo-user <oja...@li...> wrote:
> > 
> > I'd like to run a logistic regression and in addition to the coefficients it's important for me to get the standard errors to calculate t-stats, etc. Is there an efficient way to do this with oj? I tried to do it by 'hand' but v slow. Thanks 
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