I'm no expert on swarming, not used it yet. But one thing that did stand
out in my mind was the snow value. Heavy snow, of maybe a few days at a
time, 'should' tie in with 311 calls. Should the data be swarmed per
season, or break down to summer & autumn and winter & spring swarms?

On Fri, Oct 9, 2015 at 1:49 AM, Matthew Taylor <[email protected]> wrote:

> Hello NuPIC,
>
> I've got weather data that looks like this [1] for every day for the
> past several years. I'm trying to correlate this weather data with the
> number of 311 calls made in the same area over time. I'm swarming over
> a selection of weather input fields and the debris call count [2].
> Weather certainly should contribute somehow to people calling for tree
> debris pickup.
>
> So far, I have swarmed twice with the following results.
>
> #1 included "rain", "snow", "precip", and "max wind speed" and the
> field contributions looked like this:
>
> Field Contributions:
> {   u'debris': 30.163726239876382,
>     u'maxwspd': -1.373108683713905,
>     u'precip': 2.1176366006787224,
>     u'rain': 0.0,
>     u'snow': -3.0830847929189784,
>     u'timestamp_dayOfWeek': 32.13034654690986,
>     u'timestamp_timeOfDay': 3.9764609868384224,
>     u'timestamp_weekend': 15.442651796208624}
>
> The best model params returned only encoded "debris" and day of week /
> weekend. I expected "max wind speed" to contribute much more to debris
> calls.
>
> #2 included "hail", "mean wind speed", "temperature variation", and
> "precip". The field contributions after swarming looked like this:
>
> Field Contributions:
> {   u'debris': 28.19563250430966,
>     u'hail': 1.7711291936725424,
>     u'meanwindspdm': -6.274956215526072,
>     u'precip': 0.0,
>     u'tempvariation': -6.395026451990224,
>     u'timestamp_dayOfWeek': 30.21767519999757,
>     u'timestamp_timeOfDay': 1.2703697906231544,
>     u'timestamp_weekend': 13.05969551380973}
>
> Still, it seems that wind and temperature variation do not contribute
> to better predictions of debris calls. You can see all my code and CSV
> data I am swarming over here:
> https://github.com/rhyolight/multivariate-example
>
> So, a couple of questions I have now are:
>
> 1. How do I interpret the "Field Contributions"? How are those number
> calculated?
> 2. What am I doing wrong? Weather certainly does contribute to 311
> Tree Debris calls in the real world. Is my data not good enough?
>
> [1] https://gist.github.com/rhyolight/5631429c950529a7c947
> [2]
> https://github.com/rhyolight/multivariate-example/blob/master/weather_debris_data.csv
>
> Thanks in advance,
> ---------
> Matt Taylor
> OS Community Flag-Bearer
> Numenta
>
>

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