Earlier quoted context omitted.
Statistics are reductionist! Well yes, that is their purpose.
My statistics professor once told us that statistics are a shadow of the truth, not the actual truth itself.
What a caveman!
Unlearning descriptive statistics
91–95 of 95 posts
Re: Unlearning descriptive statistics
#92Earlier quoted context omitted.
Several great points (normit is the basis for the Gaussian copula, which was used to great effect to model the CDOs (collateralised debt obligations) that blew up in the GFC (global financial crisis)); but it would have been possible to raise them while being less dismissive...
Yeah, sorry about that. By the time I realized the way the tone had come off, I had managed to "noprocrast" myself off the site. I need to write better hot takes
Please do. That was a lot of interesting material, and the tone was unfortunate.
Re: Unlearning descriptive statistics
#93Earlier quoted context omitted.
Re: the linear methods vs. neural networks It depends on the domain. Logistic or most other classifiers won't get close to NN when classifying images or text. It's not 80-90% of the power. You are right when dealing with data that is not highly-dimensional and not very non-linear either. Also plenty of other domains..
Logistic won't do anything useful for text, to be sure, although an HMM often will (or if you have continuous-valued sequences, a Kalman filter often will do the same). Logistic or multinomial can be tremendously handy for picking up interactions between measurements that can be followed up on and/or expanded in the limited-data case. I think that the nonlinearity is what really sets apart problems better handled by…
Yeah totally, and I usually fall back on "classic" methods like linear and forest algorithms. It's always good to remind myself of how many domains ML is applicable to, not just image and text analysis which seems to be the hot topic of the day.
Re: Unlearning descriptive statistics
#94Earlier quoted context omitted.
Your followup post ( http://www.johnmyleswhite.com/notebook/2013/03/22/using-norm... ) is excellent. Thank you!
Thanks! I really should have finished and written the post about the SVD as well. One of these days...
I'd love to read your post on SVDs once it's written
Re: Unlearning descriptive statistics
#95I wrote an article for the ACM Queue (also published in CACM) about this very issue called "Statistics for Engineers" http://queue.acm.org/detail.cfm?id=2903468
I took a "Statistics for Engineers" course while at university. It was mostly focused around ANOVA and hypothesis testing. By the end of the course I was sick of hearing the phrase "Null hypothesis". I wish the course had introduced some more practical applications instead it was very high level and theoretical. Working as an engineer now (Materials Engineering) here is a short list from the top of my head of what I…
Thanks for your list.
In the IT Operations / Monitoring domain time series models play a large role. At the same time the level of sophistication is rather low. You definetly have to start with the basics when teaching such a course.