edgaracarneiro / feup-ecac Goto Github PK
View Code? Open in Web Editor NEWProject developed for 'Knowledge Extraction and Machine Learning', a fifth year subject @FEUP. Made in collaboration with @cyrilico.
License: MIT License
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feup-ecac's Issues
Remove redundant data (e.g. duration) and use PCA to assert the remaining features
PCA - Principal Component Analysis
Plot DT and RF Algorithms
Unir account + district com client, pelas respectivas keys
Run all prediction methods, instead of only one
Instead of forcing the User to choose a prediction method in each run, run all available and output the two models with highest performance and the respective predictions.
Fix undersampling
Experiment with under sampling
Make K folds random
I have a 1k dataset, assuming a k folda value of 0.25 we do:
- Get 250 of the 1k and run them with the other 750;
- Get 250 of the 750 and run them with the other 750;
- Get 250 of the 500 and run ..
...
For the predictions instead of only using the test files, use the test + train files
Will it get better?
Make analysis of the current algorithms, such as DT and RF
Experiment with over-sampling
MAKE PUBLIC PLS
soares is dead, long live ecac
Attempt messing with class weights on prediction algorithms
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