Posted on Mon 15 February 2016 in TDDA • Tagged with tdda, bad data
My first paid programming job was working for my local education authority during the summer. The Advisory Unit for Computer-Based Education (AUCBE), run by a fantastic visionary and literal "greybeard" called Bill Tagg, produced software for schools in Hertfordshire and environs, and one of their products was a simple database …
Continue readingPosted on Wed 06 January 2016 in TDDA • Tagged with tdda, errors, interpretation
Guest Post by Patrick Surry, Chief Data Scientist, Hopper
Every year, Expedia and ARC collaborate to publish some annual statistics about domestic airfare, including their treatment of the perennial question "How far in advance should you book your flight?" Here's what they presented in their report last year:
Although there …
Continue readingPosted on Wed 16 December 2015 in TDDA • Tagged with tdda, tools
Good tools for testing matter because the temptation to skimp on testing is real even for true believers: anything that reduces the friction and pain associated with actually adding tests therefore has a disproportionate effect on adoption and implementation rates.
I think there are several reasons the temptation to forego …
Continue readingPosted on Mon 14 December 2015 in TDDA • Tagged with tdda, errors, applicability
Everyone building predictive models or performing statistical fitting knows about overfitting. This arises when the function represented by the model includes components or aspects that are overly specific to the particularities of the sample data used for training the model, and that are not general features of datasets to which …
Continue readingWe have an overview piece in Predictive Analytics Times this week.
You can find it here.
Continue reading