### Table 1: Tennis game states

"... In PAGE 13: ... Finally, if the match has not finished, it announces the player who has to serve, and the whole scenario is repeated until the end of the match. A tennis game can be described by a set of states and transitions as illustrated in Table1 , Figure 13, and Figure 14. Table 1: Tennis game states... ..."

### Table 3. Comparative analysis of predictive ability for different neural networks

"... In PAGE 13: ... It should be noted that we also tried to leave larger fractions out, but even in the case of leave-two-out models, the predictive ability of the networks (expressed as q2) appeared to be reduced (data not shown). Different neural network architectures ( Table3 ) were automatically built as implemented in the NeuroSolution program and assessed using the LOO value. LOO works by leaving one data point out of the training set and giving the remaining instances (31 in the case of the CYP3A4 reaction set) to the learning algorithms for training.... In PAGE 13: ... A comparative LOO analysis was conducted on models trained using several different learning algorithms and the entire 24-descriptor set. The resulting values for average training (r2) and cross-validation (q2) coefficients are reported in Table3 . Among the neural networks tested, modular neural networks with 2 hidden layers provided the best predictive ability.... ..."

### Table 1: Characteristics of neural network survival analysis methods.

2005

"... In PAGE 11: ... Again, no extension is presented to deal with time-varying inputs. Discussion Table1 presents an overview of the characteristics of the neural network based methods for survival analysis discussed in the previous subsections. From the literature review above, it becomes clear that for large scale data sets, the approaches of Faraggi, Mani and... In PAGE 21: ... 3rd most imp. insurance premium insurance premium frequency paid Table1 0: Predicting default in first 12 months on oversampled data set. gives the results for loan default between 12 and 24 months.... In PAGE 21: ... Note that when comparing Tables 10 and 11 with Tables 8 and 9, it becomes clear that the oversampling allowed to correctly detect a higher proportion of bads as bad. Analogous to the previous subsection, we Actual Logit Cox NN G-predicted G 2015 1753 1744 1757 G-predicted B 0 262 271 258 B-predicted G 0 262 271 258 B-predicted B 394 132 123 136 Table1 1: Predicting default 12-24 months on oversampled data set. can also generate 3D surface plots from the neural network outputs in order to present a general view of the sensitivity of the survival probabilities with respect to the continuous inputs.... ..."

Cited by 4

### Table 7: Recommendations for Neural Network Use with Education Policy Analysis Questions

in Enhancing our Understanding of the Complexities of Education: "Knowledge Extraction from Data" using

"... In PAGE 22: ... (See Table 6) Table 6: Over and Under-representation of Asian/Pacific Island Students Group CHI FIL JAP KOR SEA PI SA WA ME OTH 1 -1% 3% -2% -4% 6% 4% -5% -1% -1% 1% 2 -1% 1% 4% -9% 5% 1% -1% -2% 4% -1% 3 0% 0% 1% 1% -3% -3% 3% 1% 1% -1% 4 9% -5% 1% 2% -7% 0% 0% -2% -2% 4% 5 -2% -3% -1% 6% -1% 0% 2% 0% -1% -1% Si milar discrepancies appear among Hispanic subgroups. Table7 suggests that the pattern of representation of the Hispanic aggregate group was substantially driven by the distribution of Mexican (MEX) students. Cuban students, to the contrary, were more likely to be found grouped with Asian/Pacific Island or White students than their Hispanic, Mexican counterparts.... In PAGE 22: ... Cuban students, to the contrary, were more likely to be found grouped with Asian/Pacific Island or White students than their Hispanic, Mexican counterparts. Table7 : Over and Under-representation of Hispanic Students Group MEX CUB PR OTHH 1 4.3% -1.... In PAGE 23: ... Yet, similar problems are likely to occur even when conventional methods are used. Table7 provides rough guidelines for applying neural networks to problems or questions related to education policy. Broadly speaking, the first two studies presented in this paper point to the particular value of hybrid neural/regression methods that apply neural or genetic algorithm estimation techniques to identify or construct a best predicting non-linear regression equation.... ..."

### Table 1: Neural network estimation results

"... In PAGE 8: ... The decision whether to use the neural net estimation or the analysis tool results can be based on a cost function re ecting the required delity and criticality of the results. Table1 shows four test results of the neural network for the aerodynamic analysis tool. Best results were obtained when the training was done for 1000 cycles with the struc- ture shown in Figure 5 and the learning rate was set to 0.... ..."

### Table 2. Results of the set of ten games played between the evolved neural network controller and the hand coded rule-based (good) controller.

2002

Cited by 8

### Table 2. Results of the set of ten games played between the evolved neural network controller and the hand coded rule-based (good) controller.

2002

Cited by 8