As Amartya Sen has stressed, Smith also wants us to evaluate our conduct from the perspective of any human being anywhere, not just a member of our own society.
For evaluating our proposed method, we have conducted tag recommendation experiments on three real datasets and the results show that the ROBIN-T algorithm achieves good performance when compared with classical approaches.
As part of the activities we have been conducting for evaluating our approach, in this work we look for any empirical evidence supporting the claim that search-based approaches improve the effectiveness and reduce the complexity of SA systems architectures.
The LOO cross validation experiment was conducted by evaluating our dual-threshold PWM scanning model using every possible pair of threshold values (where score is measured as the sum of log odd values) over the ranges t1 = {3, 3.05, 3.1…..5} and t2 = {5, 5.05, 5.1….8} to identify TREs in the 19 sequences described above.
To evaluate our approaches, we conduct extensive experiments on the selected UCI data sets across different cost ratios, and on a real world data set, KDD-98 with real misclassification cost.
To evaluate our approach we conducted two types of experiments: theoretical and practical ones.
To evaluate our approach, we conducted a controlled experiment, which showed a statistically significant improvement for knowledge acquisition of 204% compared to conventional experience descriptions.
In order to evaluate our approach, we conducted 20 collaborative design sessions with the participation of 94 undergraduate university students (aged 19 24) for eliciting requirements for the design of an ideal course website.
To evaluate our design, we conducted tests in which a robot arm used a cylindrical end effector covered with skin to slide objects and press on objects made from four different materials.
To evaluate our approach, we conducted three analyses using two systems: Health Watcher v10 [16] and PetStore v1.3.2 [17].
To evaluate our approach, we conducted several experiments that have highlighted the performance of our recommender system.
