Thank you Matthew, I'll experiment with the events. No, this will actually be a component of my final year project (4th year college, Ireland)
I missed the boat for this years challenge, but I'll be sure to join in next year! Thanks again, Alan Haverty On Tue 27 Oct 2015 at 04:23 Matthew Taylor <[email protected]> wrote: > Hi Alan, > > Here are my comments about your questions. > > 1.a. This was an ad-hoc idea, but I haven't tried it. > > 1.a.i.-ii. Ideally, you would not want to include this field at all, you > would just have years worth of data an a learned model that has seen the > patterns each holiday produced in the past. But since you don't have that > kind of history, you'll need to experiment a little. Perhaps a simple > countup isn't going to give you what you want... if a holiday like XMas is > a big deal, maybe its value is higher and there is a longer countup to that > date, rather than say St. Patrick's Day. Like I said, this was just an > ad-hoc idea and I can't say for certain how it will work. You'll want to > experiment with it. > > 2. If you have data for 15 locations, I would say that each location > should have its own model. One model only make predictions for one field, > anyway. > > 2.a. You would only lose value if there are correlations between the > locations, but I imagine this is not the case. The frequency of deliveries > at one restaurant are probably not directly affected by the frequency of > deliveries at another. > > 2.b. No. > > By the way, is this an HTM Challenge project? > > Regards, > > > --------- > Matt Taylor > OS Community Flag-Bearer > Numenta > > On Mon, Oct 26, 2015 at 1:27 PM, Alan Haverty <[email protected]> wrote: > >> Hello Nupic, >> >> >> I have some questions about feeding in known events and also, how I >> should handle multiple 'locations' that have similar properties but that >> may not be directly related in reality. >> >> >> Please let me know if I'm asking in the wrong mail list. >> >> I'm also providing a brief description and example of the project. >> Outline of Problem >> >> Restaurants that offer food delivery are forced to hire drivers, pay for >> insurance, pay for wages + predict how many drivers are needed in advance >> and schedule their hours. >> >> >> I propose to abstract this as a service where restaurants can simply use >> an app to request a driver and let this service-business worry about >> drivers, insurance, wages, roster scheduling etc. >> >> >> To achieve this, the central ‘delivery system’ needs to predict how many >> jobs are going to come from each area within a city to allow scheduling of >> drivers days/weeks in advance. >> >> >> I believe NuPIC is ideal to solve this problem, but I have a few >> questions that I hope the mailing list can help with. >> >> >> *Assuming for this example:* >> >> - That a city is divided into 15 geographical areas. >> - That I have 3 months of known data with the amount of total >> deliveries that came from each area per hour. >> - That I need to predict the number_of_deliveries per hour (days/week >> in advance, not too concerned with how far in advance yet.) >> >> Example Data >> >> *Example of 3hrs of data for one of those 15 areas:* >> >> *dttm* >> >> *number_of_deliveries* >> >> *datetime* >> >> *int* >> >> *T* >> >> 2015/08/01 00:00:00.0 >> >> 178 >> >> 2015/08/01 01:00:00.0 >> >> 96 >> >> 2015/08/01 02:00:00.0 >> >> 52 >> >> >> Questions >> >> 1. 1. If I want to incorporate event data for known upcoming events >> such as a national holiday/football game/TV series finale airing; how >> should this hourly event data be arranged? >> >> a. Matthew Taylor suggested >> <https://www.youtube.com/watch?v=gYOwBlVuJDw> to use a count down until >> the hours of the event >> >> i. How >> would this work if I wanted to weight certain events differently? (e.g. A >> national bank holiday would be weighted higher than a television series >> episode airing) >> >> ii. While >> the event is occurring, how should the countdown be represented? Should it >> be ..,5,4,3,2,1,1,1,1,1,…,1,20,19,.. *(Red being the event currently on >> for that hour(s) or some cases the whole day(s))* >> >> 2. 2. I need to do this for multiple locations, would a field to >> specify each location be correct (Meaning there would be x15 {Saturday @ >> 12:00}, *one for each of the 15 locations*) or should they be totally >> separated? >> >> a. If I separate locations completely, would you expect I lose >> value in anyway? >> >> b. If I keep them together, could locations contaminate/effect each >> other that may not happen in reality? >> >> *c. **Apologies for this broad question, if anyone could even >> point me to suggested reading, I would appreciate it.* >> Thank you for reading! >> >> >> >> *Best regards, Alan Haverty**[email protected] <[email protected]>* >> >> >
