| Technique |
Decision Trees |
Neural Networks |
Naive Bayes |
Instance Based |
Genetic Algorithms
| Rule Learning
| Final: Neural Networks
|
| Best accuracy |
86.0881 |
77.1329 |
84.2700 |
81.3893 |
76.8932 |
81.3341 |
84.3806 |
| Code (mine/other/adapted) |
Weka |
Adapted from Book |
Adapted Weka |
Adapted Weka (nearest neighbor) |
Mine (and it shows) |
FOIL (Quinlan) |
Adapted from previous |
| Programming Language |
Java |
Java |
Java |
Java |
Java |
C |
Java |
| Num. of training instances |
32561 |
500 |
32561 |
32561 |
515 |
32561 |
32561 |
| Num. of test instances |
16281 |
16281 |
16281 |
16281 |
16281 |
16281 |
16281 |
| Missing values included?(y/n) |
Yes |
Yes |
Yes |
Yes |
Yes |
Yes |
Yes |
| Number of attributes used |
All |
All |
All |
All |
All |
All |
All |
| Best thing about this project |
-Good intro
-Tree display
|
-Cool sounding
-Expect good accuracy
-Writing it
|
-Simple concept
-Simple code
-Good initial results
|
-Extended code
-Case based reasoning
-Comparable - Weka's IBk
|
-Tried novel approach
-Discussion despite results
|
-Impressive system
-Difficult by hand
-Excellent readability
|
-Verified functionality
-Accuracy better
-Complex behavior fun
|
| Worst thing about this project |
-Lack expectations
-Didn't know if accuracy was good
|
-Poor accuracy
-Verifying functionality
|
-Tuning less apparent
-Explaining Std. Dev., mean for num. att.
|
-Time lacking : more tests
|
-Poor results
-Uncompleted (short-sighted) system vision
|
-Jargon ignorance = confusion
-No Java port time ;)
|
-Run time
-Complex behavior (no play time)
|
| Other comments |
Compare tree and FOIL rules
|
Needed save/load
|
|
|
|
|
Still need save/load
|
