predictive model for user behaviors

1. Howstressedwillyoubeinthe
nexttwohours?
Xin Chen
Data source: Spire Inc

2. Whatisspire?
Spire wants to be your
mindfulness guide!
Tense
Focused Calm
Neutral

3. Today
16:00 - 18:00
Time to work hard!
predictive model

4. 00:00:00 24:00:00
calm focused focused tense tense
16:00:00 18:00:00
0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0
16:00:00 18:00:00
# of minutes being tense

5. 00:00:00 24:00:00
calm focused focused tense tense
16:00:00 18:00:00
16:00:00 18:00:00
Prior information: the past 10 days
Posterior: # of minutes being tense today?
Posterior (# of minutes tense 16:00-18:00 today) =
Prior(# of minutes tense 16:00-18:00 in previous 10 days)* Lik(today)
Comparing # of minutes tense 16:00-18:00 today to user’s tense baseline

6. Prior
Today
16:00 - 18:00
Time to work hard!
mindtrainr.tech
# of minutes being tense 16:00-18:00 (in proportion)
67% accuracy

7. XinChen
Computational Biology Postdoc Computational Biology PhD

8. XinChen
Computational Biology Postdoc Computational Biology PhD

9. 0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0
Modelsetup
00:00:00 24:00:00
16:00:00 18:00:00
tense
16:00:00 18:00:00
16:00:00 18:00:00
?
1. Within given time range, how many minutes is likely to be tense for this user?
1. Is the total time of being tense within the 120 mins significantly higher/low than the user’s average level?
today
the past 10 days

10. BayesianfunctionandMarkovChainMonteCarlo
PosteriorProbability(tensebetween16:00-18:00)
=Prior*Lik
Searching for the maximum values
for posterior probability
● Multiple chains
● One million generations
● Test convergence

11. Convergence
effective sample size is {'p': 833}
effective sample size is {'p': 614}
effective sample size is {'p': 579}
Gelman_rubin test:
{'p': 0.9997 }
{'p': 0.9997 }
{'p': 0.9997 }
Geweke test

12. Posteriordistribution
Calm
Focus
Tense