Hello,
Now, I have just started to explore predictive possibilities of NuPIC.
Although I believe these are very basic questions for predictive functions of
NuPIC that you may be already understanding, I would appreciate if someone
could advise or give answers to the following questions regarding the sample of
Hot Gym Prediction and CPU sample.
------------------------------------------------------------------
<1> Hot Gym Prediction
------------------------------------------------------------------
Q1 : Is it possible to lead to answers at one time as predicted data,
anomalyScore and anomalyLikelihood by feeding different data streams acquired
from different data sources such like GYM1, GYM2 or GYM3?
[Input data]
GymID Date Consumption
GYM1 2/5/2015 0:00:00 21.2
GYM2 2/5/2015 0:00:00 12.3
GYM3 2/5/2015 0:00:00 31.5
GYM1 2/5/2015 1:00:00 16.4
GYM2 2/5/2015 2:00:00 11.8
GYM3 2/5/2015 3:00:00 30.5
: : :
: : :
GYM1 2/5/2015 23:00:00 11.2
GYM2 2/5/2015 23:00:00 2.3
GYM3 2/5/2015 23:00:00 21.5
[Desirable Output] (Prediction)
GymID Date Consumption anomalyScore
anomalyLikelihood
GYM1 2/6/2015 1:00:00 16.3 0 0.5
GYM2 2/6/2015 1:00:00 11.5 0 0.3
GYM3 2/6/2015 1:00:00 29.1 0 0.2
Q2 : In addition to above, how I could write scripts with JSON to execute swarm
in case of the model_params which predicts analytics results above?
------------------------------------------------------------------
<2> CPU Sample
------------------------------------------------------------------
Q1 : Is it possible to lead to answers at one time which are categorized by
different parameters by feeding data streams obtaining these parameters such
like CPU(%), Memory(GB)and DISK_USAGE(GB) as shown below?
[Input data]
CPU(%) Memory(GB) DISK_USAGE(GB)
12.3 75.6 250.4
15.6 68.5 251.3
13.7 71.6 251.8
[Desirable Output] (Prediction)
CPU(%) Memory(GB) DISK_USAGE(GB)
14.8 69.7 252.1
Q2 : In addition, how I could write scripts with JSON to execute swarm in case
of the model_params which predicts analytics results above?
Thank you for your help.
