Figure 4

Comparison of the learning curves of six different structure learning algorithms. For each learning algorithm, the results of the comparison of the graph learnt for various sample sizes and the reference graph are expressed in terms of positive predictive value (A) and sensitivity (B). The color coding is green for Greedy search, blue for MCMC, black for K2, dashed black for MMHC, magenta for TPDA, and red for EA. For each sample size, tests are performed on 10 different and independent datasets. The same datasets are used for every algorithm. Each point along the curves, which correspond to a given sample size, presents the mean value and the standard deviation of the quality measurement across the 10 runs of the algorithm.