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Table 6. Maximum and Mean Value of the Count Values Across the Count Fingerprints of the Sample of 50 000 Molecules from ChemDBa
2007
TABLE 1 ARRE AND MRRE OF THE SEMI-LOGARITHMIC NUMBER SYSTEMS FOR DIFFERENT VALUES OF k
1998
Cited by 2
Table 6: The average number of local optimizations ran during one execution of RANSAC and logarithm of average number of samples for comparison.
"... In PAGE 18: ... Note, that this is the upper bound as the number of correspondences is finite and discrete and so the same number of inliers will occur often. This theoretical bound was confirmed experimentally, the average numbers of local optimization over an execution of (locally optimized) RANSAC can be found in Table6 . For more details about experiments see Section 4.... In PAGE 21: ... to E. The results for 100 runs are summarized in Table 5. For each experiment, a table containing the average number of inliers, average number of samples drawn, average time spent in RANSAC (in seconds) and efficiency (the ratio of the number of samples drawn and expected) is shown. Table6 shows both, how many times the local optimization has been applied and the theoretical upper bound derived in Section 4.1.... ..."
Table 1. Number of elementary operations to implement Zech logarithms for an odd characteristic
"... In PAGE 3: ... This table gives the exponent h of any number of the form 1 + gk, so that gh = 1 + gk. Table1 shows the number of elementary operations to implement Zech logarithms for an odd char- acteristic finite field. Only one table of size q is considered.... ..."
Table 2 Dependent variable: change in Logarithmic real bolivares Number of observations 7744
"... In PAGE 20: ...ncluded in vectors Xi,t-1 and Zi (i.e., initial characteristics and observable time- invariant characteristics).11 Table2 presents the estimation results from the 1997-1998 panel. The first column corresponds to a regression of the dependent variable on lagged family income per head only; the second column includes initial characteristics of the head and of the household itself.... In PAGE 21: ...e. single with children, single without children, couple without children and multi-family) are not significantly different from zero in columns 2, 3 and 4 of Table2 . What matters for income changes is the amount and quality of available human capital in the household.... In PAGE 35: ...Samuel Freije / Income, Positional and Poverty Dynamics in Venezuela 33 Table2 (cont.) Some private transfers 0.... In PAGE 36: ...Samuel Freije / Income, Positional and Poverty Dynamics in Venezuela 34 Table2 (cont.) Marriage x change in non-head informal workers -0.... ..."
Table 2 Results of the 10 folds including: average number of instances in the test set; average of the logarithmic score; and number of wins and losses between N-SAPS and the local logistic regression (LLR) model
2003
"... In PAGE 15: ... The performance of N-SAPS is also inspected for that fold on these nodes. The results of the experiments are shown in Table2 where the columns correspond to the nodes considered. The second row provides the average number of instances in the 10 folds, along with the standard deviation.... In PAGE 15: ...f their mortality. When several patients have the same scores, all of them are included. The 5-NN model has been outperformed in every node in any fold by each of N-SAPS and LLR. The results in Table2 show that for each of the nodes C, E, H, and I, the performance of the local models has been clearly better: for the nodes C, E, and H the local models have outperformed the N-SAPS model in 8 out of the 10 folds. The local models have also outperformed N-SAPS in 7 out of the 10 folds for the node I.... In PAGE 17: ... It was also interesting to inspect how non-parametric local regression models would compare to the logistic regression models. As could be seen from Table2 , the 5-NN model was clearly inferior to the parametric models. However, when we conducted experiments in which we used Lowess on the training set as basis for predictions on the test set, the results were mixed.... ..."
Table 4.1: The three prototype databases. Shown is the number of classes in each database, and the logarithm of base two of the number of classes, which represents the minimum number of binary questions required to separate the classes.
Table 1 lists the code that was used to construct Figure 3, in which the common logarithm of the number of words Shakespeare used exactly n times is graphed versus n for n = 1, 2, . . . , 100. In tabular form the data are as follows:
1988
"... In PAGE 17: ... TeX apos;s preloaded fonts. Table1 contains the sixteen fonts named in plain. TeX.... In PAGE 17: ... These are the sans serif fonts, cmsslO (Table 2) and cmssl7 (Table 4). In Table1 it is shown that IPT@ uses cmrlO scaled to \magstep5. I think it would have been more consistent to have made the larger fonts from lesser scaling of cmrl7.... In PAGE 17: ... See the last section of this article for more discussion on font design sizes. Table1 . The Bin Sixteen The fonts in Table 2 are required by IPl$jX.... In PAGE 17: ... The Bin Sixteen The fonts in Table 2 are required by IPl$jX. These are all the fonts required by IP apos; except for those already indicated in Table1 . (I tried to make sure that each font appeared in only one table.... In PAGE 18: ... These fonts should be considered optional in most installations. Some of these fonts could be provided at larger magnifications to complement the title fonts shown in Table1 . The font cmssl7 is listed here and is furnished in large magnifications for use in titles.... In PAGE 82: ...Figure 3 has n on the horizontal (x) axis, and A, on the vertical (y) axis. Table1 . PlCQ$ commands for Figure 3.... In PAGE 82: ...1576 13 \setplotarea x from 0 to 100, 14 y from 0 to 4.301 15 \axis bottom 16 label {Frequency $n$ of usage) 17 ticks numbered from 0 to 100 by 20 18 short unlabeled quantity 11 / 19 \axis left shiftedto x=-5 20 label {\stack 2 1 CN,u,m,b,e,r,, ,o,f,, ,w,o,r,d,s}l 22 ticks logged 23 numbered at 1 10 100 1000 I0000 / 24 unlabeled short from 2 to 9 by 1 25 from 20 to 90 by 10 26 from 200 to 900 by 100 2 7 from 2000 to 9000 by 1000 28 at 20000 / / 29 \endpicture Table1 is largely self-explanatory, since much of the code reads almost like English. However, some remarks are in order: (1) The command on line 2 tells PJCI$J to set up a rectangular coordinate system in which one unit on the x axis has length of .... ..."
Table 3: Results of performing a regression on the (logarithm of) number of iterations for Algorithm 1. 68% of the variation in time per iteration is explained by the regression model. The di erent columns are as explained for Table 7.
Table 1 Cats. Relations between evaluated parameters and oral health index Evaluated Number Ratio [%] LSM Logarithm Signifi cant SE
"... In PAGE 16: ...4% cats (3632). The results regarding each of evaluated parameters are presented in Table1 (cats) and Table 2 (dogs) All parameters were adjusted to the mean age that in cats was 4,801 yrs and in dogs 5,758 yrs. The most signifi cant infl uencing parameter on oral heath status has the age.... ..."
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