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.
>
