Week 5 Demo

Transcript

2. Goal  of  We  Lose  it   •  Misinforma1on  about  weight  loss   •  Goal  of  We  Lose  It   – Reasonable  goals   – Ac1onable  items   – Using  historical  data  
3. Demo  
4. Weight  Informa1on  Dataset   Sex   Age   Height   Username   Start   Weight  (lbs)   End  Weight   (lbs)   Time   Elapsed   Title   Keywords   M   34   6’   randomt2000   299   277   5  months   Eat,  running   Total  Users:  3  
5. Predic1ng  Weight  Loss   Actual  vs.  Predicted  Weight  Change   •  Linear  Regression  to   predict  weight  loss   •  Quality  metrics   –  R2   =  0.61   –  RMSECV  =  23.4  lbs   –  Null  Deviance:  37  lbs   Actual  Weight  Loss  (lbs)   Predicted  Weight  Loss  (lbs)   Feature   Coefficient   Value   Start  Weight   (lbs)   0.51   Height  (lbs)   -­‐1.9  
6. *   Data  Mining:  Nega1ve  Sen1ments   Mean  ±  standard  error   High  Sen1ment:  47.4  ±  1.4  lbs   Low  Sen1ment:  59.9  ±  3.3  lbs   *  p  <  0.05  
7. Data  Mining:  Pos1ng  at  the  right  subreddits   •  For  all  users,  the  average  weight  loss  was  58  lbs  but  users   who  comment  at  r/loseit  lose  79  lbs  on  average   (Weighted  by  #  of  1mes  posted)  
8. •  d  
10. T-­‐Test:  June  vs.  Other  Months   Jan:  p  =  0.773   Feb:  p  =  0.056   Mar:  p  =  0.0529   Apr:  p  =  0.000930   May:  p  =  0.162   Jun:  p  =  1.0   Jul:  p  =  0.0340   Aug:  p  =  0.0999   Sep:  p  =  0.0533   Oct:  p  =  0.00181   Nov:  p  =  0.00918   Dec:  p  =  0.4936  
12. Data  Mining:  Ac1onable  Items   •  Start  in  the  off  season   –  June  was  the  worst  month  to  lose  weight  
13. TF-­‐IDF   •  Compared  terms  used  by  people  who  lost   more  than  70  lbs  vs.  less  than  30  lbs   Word   Increased  frequency  in   larger  weight  loss   weight   0.036   game   0.029   exercise   0.019   keto   0.018   diet   0.016   calorie   0.016   goal   0.013   skin   0.010   Word   Increased  Frequency  in   smaller  weight  loss   girl   0.018   boyfriend   0.016   friend   0.016   love   0.013   rela1onship   0.012   mom   0.012   baby   0.011   school   0.010  
14. Residuals   •  d