@Chandan In your example sequence 1, it seems that "AAABXY" is repeatedly followed by itself. It will then be treated as a high-order sequence. So the second time it sees B in sequence 1, it will only predict "X".
However, if the subsequence "AAABXY" and "AAABCD" are randomly interleaved, temporal memory won't be able to learn the "AAABXYAAABXY" as a high-order sequence. I think it will predict both "C" and "X" after then 2nd B in that scenario. Yuwei On Fri, Aug 7, 2015 at 12:28 PM, cogmission (David Ray) < [email protected]> wrote: > Its true that after repeated submissions of the two sequences, the > Classifier will vote on X or C's bucket with more reliability. Otherwise, > from what I understand, the TemporalMemory will look for active segments > leading from its active cells (cells in the column(s) indicating "B"), to > see which Segments have Synapses who's permanence is above minThreshold, > and those will be the "predicted" Synapses; and those post-synaptic cells > will be the predicted cells - which belong to columns indicating the > TemporalMemory's next prediction after "B". > > How's that for confusion? :-) > > > > On Fri, Aug 7, 2015 at 2:00 PM, Chandan Maruthi <[email protected] > > wrote: > >> @cogmission >> If thats right i get it, but it doesnt make sense at the the 2nd B you >> should know that there is a high probabilty of X or C based on the most >> recent context >> >> >> >> >> On Friday, August 7, 2015, cogmission (David Ray) < >> [email protected]> wrote: >> >>> Hi Chandan, >>> >>> He's saying that nothing determinant can be predicted at B - and all >>> possible sequences that are equally predictable will therefore be predicted >>> because at B, both sequences are ambiguous or equally probable. >>> >>> Does that help? >>> >>> >>> On Fri, Aug 7, 2015 at 1:10 PM, Chandan Maruthi < >>> [email protected]> wrote: >>> >>>> Yuwei, >>>> So you you are saying that at the 2nd B it should be able predict if >>>> its in the X or C sequence is that right? How does this work? >>>> >>>> >>>> On Friday, August 7, 2015, Yuwei Cui <[email protected]> wrote: >>>> >>>>> Hi Chandan, >>>>> >>>>> It is not possible to disambiguate the two sequences at the >>>>> highlighted B. So NuPIC will predict both C & X at that point. However, >>>>> only one of the predictions will be confirmed at the next step. So if we >>>>> are indeed in sequence 1, it will predict only Y after X, and vice versa. >>>>> >>>>> In other words, TM handles branching temporal sequences by >>>>> maintaining predictions about multiple possible inputs until there is >>>>> sufficient disambiguating evidence. Does it make sense? >>>>> >>>>> Yuwei >>>>> >>>>> On Fri, Aug 7, 2015 at 10:09 AM, Chandan Maruthi < >>>>> [email protected]> wrote: >>>>> >>>>>> Question on Synaptic Connections >>>>>> Consider 2 sequences >>>>>> >>>>>> Sequence 1: AAA*BXY*AAA*BXY*AAA*BXY* >>>>>> Sequence 2: AAA*BCD*AAA*BCD*AAABCD >>>>>> >>>>>> >>>>>> Consider the B highlighted, how does Nupic know that it is in >>>>>> sequence 1 vs sequence2 >>>>>> when the transition from A to B happens, how does it know that it is >>>>>> in the ABX sequence vs ABC. Also once it starts seeing ABX vs ABC, how >>>>>> does >>>>>> it know that the ABX sequence is more relavant at the moment.. >>>>>> >>>>>> >>>>>> -- >>>>>> Regards >>>>>> Chandan Maruthi >>>>>> >>>>>> >>>>> >>>> >>>> -- >>>> Regards >>>> Chandan Maruthi >>>> >>>> >>>> >>> >>> >>> -- >>> *With kind regards,* >>> >>> David Ray >>> Java Solutions Architect >>> >>> *Cortical.io <http://cortical.io/>* >>> Sponsor of: HTM.java <https://github.com/numenta/htm.java> >>> >>> [email protected] >>> http://cortical.io >>> >> >> >> -- >> Regards >> Chandan Maruthi >> >> >> > > > -- > *With kind regards,* > > David Ray > Java Solutions Architect > > *Cortical.io <http://cortical.io/>* > Sponsor of: HTM.java <https://github.com/numenta/htm.java> > > [email protected] > http://cortical.io >
