Sunday, August 22, 2010

Agenda, August 24

Stuff in blue shows addits after posting0.
Stuff in green shows addits after posting1.

- need to name our desk. landscape paper, name in 30 point, photo.
- we now have 2 sets of ugrads students working the 

- range experiment, and on other data sets.
- need that graphic max wanted showing the complexity of our data
- thesis outline (on paper).

- can you attend? want to talk abut china and java W

- all the latexing of the e,d,m and edm results done.
- ditto with the discretization experiments. outline of thesis.
- thesis outline (on paper)
- co-ordination with adam re java W
- need a revision of the paper that shows a good example of instability and
how it is less with W2
- receipt from japan

- when you used "log" pre-preprocessor, did you unlog afterwards before (say) MRE?
- check jacky's TSE corrections
- the abstract only mentions MRE. add others? or delete reference to MRE?
- check that our quotes from the paper in the review section are still accurate
- FIG5: when you checked (median(a) < median(b)), did you reverse that for pred?
- needs a bridge at end of 3.2. As can be seen in this example, it is not necessarily true that moving to a smaller set of neighbors decreases variance. As shown below, it can improve prediction accuracy if ABE takes this matter into account.
- bring (small) copies of ASE poster
- revist all old results. which need to be done with strong data sets?
- need your full passport name
- can we do ensembles just as a simple TEAK extension? just by randomly selecting from the current sub-tree 90%, 10 times?

- (the following will take some time)
- redo the icse paper's results with
- compass
- (sum, pred25, mre)
- win%,loss%, (win-loss)%
- leave-1-one, cross-val
- china broken up. jacky says it naturally divides into a few large chunks. chinaA, chinaB, etc.
- report the number of rank positions things change.
- i.e. what is expected wriggle in an algorithm's rankings
- a simple MSR paper

- seeking results on
- splitting data in half
- building a predictor (?teac) from one half
- walking the other one half in in (say) 10 eras
- after clustering the other half from era[i], find the most informative regions to query and send those queries to the predictor
- extend the era[i] cluster tree with the new results found during (c)
- test the new tree on era[i+i]
- increment "i" and goto (c)

- photos, videos of the helicopter on the blog
- Effort Estimation Experiments with Compass and K-means
- Code is ready to go (Thanks in very large part to Andrew's previous work)
- Want to discuss experiments about effort estimation and defect predictions.
- Working on Matlab versions of TEAK and Compass to work with Ekrem's Matlab rig later.

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