New Figure (Oct 6st)

[azhe825]

25 repeats, took about 1 day on ncsu hpcc.

Hall Result

Hall, Tracy, Sarah Beecham, David Bowes, David Gray, and Steve Counsell. "A Systematic Literature Review on Fault Prediction Performance in Software Engineering."

	Hall Paper	IEEExplore
Initial Size	2073	8912
Final Size	136	106

Wahono Result

Wahono, Romi Satria. "A systematic literature review of software defect prediction: research trends, datasets, methods and frameworks." Journal of Software Engineering 1, no. 1 (2015): 1-16.

	Wahono Paper	IEEExplore
Initial Size	2117	7002
Final Size	71	62

Question: is the figure clear enough? or make it double with medians and iqrs on different figs?

Comparisons for each code:

P_U_S_A vs. P_U_S_N P_U_S_A wins. For last code, A is better than N (aggressive undersampling is useful)

Compare the third code P_U_S_A vs. P_U_C_A No clear winner. C is better than S due to its ability to continuous update the model.

Compare the second code P_U_C_A vs. P_C_C_A No clear winner, let's keep both.

Compare the first code P_U_C_A vs. P_C_C_A vs.H_U_C_A vs. H_C_C_A H is better than P. H_U_C_A and H_C_C_A are similar.

Compare H_U_C_A and H_C_C_A in terms of stability:

H_C_C_A outperforms H_U_C_A in terms of stability.

Comparing to state-of-the-art: H_C_C_A vs. H_C_C_N vs. P_U_S_A

H_C_C_A outperforms either of the state-of-the-art methods.