Yes, I would say typically that more fields == more spatial.

---------
Matt Taylor
OS Community Flag-Bearer
Numenta

On Tue, Jan 12, 2016 at 4:30 AM, Wakan Tanka <[email protected]> wrote:

> Thank you Matt,
> so basically you can have various combinations of datasets and also the
> nature of data in that dataset can vary, I mean you can have highly spatial
> or less spatial dataset etc. Is this correct?
>
> Thanks
>
>
>
> On 01/11/2016 07:52 PM, Matthew Taylor wrote:
>
>> Spacial == "space"
>> Temporal == "time"
>>
>> Our reality plays out in "spacetime", meaning each frozen moment in time
>> contains a spatial representation, and each moment is a part of a
>> sequence of moments that constantly changes.
>>
>> If you had a data stream of one scalar value over time, like temperature
>> for example, this would be considered a highly temporal pattern because
>> there is only 1 spatial dimension. Just one value changing over time.
>> Adding more fields of data to this temporal stream adds spatial
>> dimensions.
>>
>> A temporal stream with highly spatial data within it would be an
>> aircraft moving through space. Each point in the flight could have
>> hundreds of data points associated with it (lat, lon, altitude, engine
>> temp, airspeed, pitch, yaw, heading, etc.). I would consider this data
>> stream to be both temporal and spatial in nature.
>>
>> HTM can identify spatial patterns in temporal data streams. Many other
>> ML technologies can identify spatial patterns in one "moment" in time,
>> like a photograph (classifying objects).
>>
>>
>> ---------
>> Matt Taylor
>> OS Community Flag-Bearer
>> Numenta
>>
>> On Mon, Jan 11, 2016 at 6:29 AM, Jeff Fohl <[email protected]
>> <mailto:[email protected]>> wrote:
>>
>>     Wakan -
>>
>>     I think you are getting there. In regard to your questions:
>>
>>      1. Spatial concepts are building blocks for temporal ones? - Yes,
>>         essentially. One way of describing it is that "spatial" refers
>>         to "things" and "temporal" refers to "things over time". So,
>>         your "thing" could be a musical note, a word, or even an
>>         abstract concept. A temporal series is simply these things put
>>         into a series.
>>      2. Yes, you could have data that is non-temporal, but it wouldn't
>>         be of much use to NuPIC. You could also have data that is just
>>         time (say, a bunch of timestamps), but that wouldn't be of much
>>         use either.
>>      3. Yes, encoders (within the context of HTM) will produce a spatial
>>         representation of something, which then can be fed into an HTM
>>         model.
>>
>>     I sense that you are getting hung up on the word "spatial". This is
>>     not a NuPIC jargon word. It is more of a mathematics jargon word.
>>     Think about how you might describe a physical object in "space",
>>     mathematically. For a cube, you might describe its volume as X^3,
>>     where X is the length of a side. Nowhere are you mentioning time, or
>>     how the cube might change over time. In this situation, all you are
>>     concerned with is with describing its static, non-temporal
>>     characteristics. Thus, you are describing its "spatial" qualities.
>>     If you were to start describing the cube's position over time as it
>>     moves through space (say, after you give it a push), then you would
>>     be talking about its temporal characteristics.
>>
>>     I hope that helps.
>>
>>     - Jeff
>>
>>     On Sun, Jan 10, 2016 at 1:18 PM Wakan Tanka <[email protected]
>>     <mailto:[email protected]>> wrote:
>>
>>         Thank you Jeff,
>>         this is clear example. May I ask regarding Matt's tutorials on
>>         youtube:
>>         1. sine waves
>>         2. hotgym prediction
>>         3. audio stream analysis
>>         4. geospatial tracking
>>         5. traffic anomalies
>>
>>         what is spatial/temporal in those cases? I guess:
>>         1.
>>         - temporal - the sines periods
>>         - spatial - building blocks of those period
>>
>>         2.
>>         - temporal - patterns representing day, week, year (those that
>>         you can
>>         see repeating when you look at plot).
>>         - spatial - building blocks of temporal
>>
>>         3.
>>         - temporal - sequence of spatial
>>         - spatial - depends on encoder (you might or not consider of
>>         changing
>>         e.g. volume or instruments in audio I do not know what all was
>> Matt
>>         considering)
>>
>>         4.
>>         - spatial - vectors
>>         - temporal - everything that is composed of vectors
>>
>>         5.
>>         - spatial - ???
>>         - temporal - ???
>>
>>
>>         Is this assumptions correct:
>>         1. From your post I've understood that spatial are building
>>         blocks for
>>         temporal?
>>
>>         2. I guess that it is possible to have data where you have just
>>         spatial
>>         data but not temporal (when you play chords at random), but not
>>         vice versa?
>>
>>         3. Spatial is heavily depended on encoder and temporal are just
>>         logical
>>         consequence?
>>
>>
>>         Thank you
>>
>>
>>
>>         On 01/10/2016 09:26 PM, Jeff Fohl wrote:
>>          > Wakan -
>>          >
>>          > Perhaps a music analogy would be useful.
>>          >
>>          > Say you are playing a series of chords on a piano.
>>          >
>>          > Some of the chords are similar, some are not. Think of each
>>         chord as a
>>          > pattern. This is a "spatial" pattern. The term "spatial"
>>         perhaps is
>>          > confusing because one tends to think of physical space when
>>         hearing that
>>          > term.
>>          >
>>          > "Temporal" refers to patterns over time. So, the sequence of
>>         the chords
>>          > is a "temporal" pattern.
>>          >
>>          > Does that help?
>>          >
>>          > - Jeff
>>          >
>>          > On Sun, Jan 10, 2016 at 12:16 PM Wakan Tanka
>>         <[email protected] <mailto:[email protected]>
>>          > <mailto:[email protected] <mailto:[email protected]>>>
>> wrote:
>>          >
>>          >     Thanks David,
>>          >     To be honest it did not help much :-( some example would
>>         be fine.
>>          >     Thank you
>>          >
>>          >
>>          >     On January 10, 2016 8:28:41 PM CET, David Ray
>>          >     <[email protected]
>>         <mailto:[email protected]>
>>         <mailto:[email protected]
>>         <mailto:[email protected]>>> wrote:
>>          >
>>          >         Hi Wakan,
>>          >
>>          >         This definition may be useful:
>>          >
>>          >         Spatial = the relative "nearness" of two data points
>>         in terms of
>>          >         their semantic (characteristics of "meaning")
>> attributes.
>>          >
>>          >         Temporal (more accurately; Sequential) = refers to
>>         patterns in
>>          >         "encounter order" pertaining to discrete units of
>> input.
>>          >
>>          >         Was that helpful?
>>          >
>>          >         Cheers,
>>          >         David
>>          >
>>          >         Sent from my iPhone
>>          >
>>          >         On Jan 10, 2016, at 6:36 AM, Wakan Tanka
>>         <[email protected] <mailto:[email protected]>
>>          >         <mailto:[email protected]
>>         <mailto:[email protected]>>> wrote:
>>          >
>>          >>         Hello Matt,
>>          >>         Can you please clarify differences between temporal
>> and
>>          >>         spatial data? I've never really get into. Thank you
>>         very much.
>>          >>
>>          >>         On January 7, 2016 6:32:37 PM CET, Matthew Taylor
>>          >>         <[email protected] <mailto:[email protected]>
>>         <mailto:[email protected] <mailto:[email protected]>>> wrote:
>>          >>
>>          >>             Divyang,
>>          >>
>>          >>             NuPIC can run on OS X and Linux (we test on
>>         Ubuntu), and
>>          >>             Windows (if you have your compilers installed
>>         properly,
>>          >>             see the READMEs).
>>          >>
>>          >>             If by "local and global" anomalies, you mean
>>         discrepancies
>>          >>             in short-term patterns vs long-term patterns,
>>         then yes.
>>          >>             For example, a change in hourly patterns would
>>         be just as
>>          >>             anomalous as a change in daily patterns.
>>          >>
>>          >>             Real-time or batch is supported, but the data
>>         should be
>>          >>             temporal in nature, not entirely spatial.
>>          >>
>>          >>             ---------
>>          >>             Matt Taylor
>>          >>             OS Community Flag-Bearer
>>          >>             Numenta
>>          >>
>>          >>             On Thu, Jan 7, 2016 at 12:14 AM, Divyang Shah
>>         via nupic
>>          >>             <[email protected]
>>         <mailto:[email protected]> <mailto:[email protected]
>>         <mailto:[email protected]>>>
>>          >>             wrote:
>>          >>
>>          >>
>>          >>
>>          >>                 ---------- Forwarded message ----------
>>          >>                 From: Divyang Shah <[email protected]
>>         <mailto:[email protected]>
>>          >>                 <mailto:[email protected]
>>         <mailto:[email protected]>>>
>>          >>                 To: "[email protected]
>>         <mailto:[email protected]>
>>          >>                 <mailto:[email protected]
>>         <mailto:[email protected]>>"
>>          >>                 <[email protected]
>>         <mailto:[email protected]> <mailto:[email protected]
>>         <mailto:[email protected]>>>
>>          >>                 Cc:
>>          >>                 Date: Thu, 7 Jan 2016 08:08:15 +0000 (UTC)
>>          >>                 Subject: some information for nupic anomaly
>>         detection
>>          >>                 hi,
>>          >>
>>          >>                 what are the different os and other
>>         configuration
>>          >>                 support require for this project of anomaly
>>         detection?
>>          >>                 do you detect both local & global anomaly?
>>          >>                 it supports only for real-time data or also
>>         support
>>          >>                 anomaly detection for batch data?
>>          >>
>>          >>                 Thanks,
>>          >>                 Divyang Shah
>>          >>
>>          >>
>>          >>
>>          >>         --
>>          >>         Sent from my Android device with K-9 Mail. Please
>>         excuse my
>>          >>         brevity.
>>          >
>>          >
>>          >     --
>>          >     Sent from my Android device with K-9 Mail. Please excuse
>>         my brevity.
>>          >
>>
>>
>>
>>
>
>

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