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]
<mailto:[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]>
<mailto:[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]>
<mailto:[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]>>
> <mailto:[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]>>
<mailto:[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]>>
> <mailto:[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]>>
<mailto:[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]>>
<mailto:[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]>>
>> <mailto:[email protected]
<mailto:[email protected]>
<mailto:[email protected]
<mailto:[email protected]>>>>
>> To: "[email protected]
<mailto:[email protected]>
<mailto:[email protected]
<mailto:[email protected]>>
>> <mailto:[email protected]
<mailto:[email protected]>
<mailto:[email protected]
<mailto:[email protected]>>>"
>> <[email protected]
<mailto:[email protected]>
<mailto:[email protected]
<mailto:[email protected]>>
<mailto:[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.
>
