Sentence examples for rules we obtained from inspiring English sources

By application of segmentation rules, we obtained a total of 6,908,655 short (300+ words) text segments - documents - entering to the process of text classification.

As shown in the experiment results, when applying Apriori algorithm or its derivatives on a dataset, we obtained 27 extracted rules, and when applying multi-criteria analysis approach on a set of extracted rules, we obtained only six significant and interesting rules.

After applying these rules, we obtained a better performance, where the MCC has increased from 0.48 to 0.50.

Using these decision rules, we obtained (blinded) clinical input to determine whether data/decision rules reflected expected clinical dosing distributions.

Moreover, under two regularization parameter choice rules, we obtain Hölder type error estimates.

From the fuzzy rules, we obtain outputs, which are used to make decisions.

Hence, for each rule we obtained the average number of contacts between pairs of substructures in matching proteins and the standard deviation indicating the stability of these contact surfaces over different proteins.

By the multiplicative update rule, we obtained the following update rules for h i,z: (5) h i, z ← h i, z 2 + 1 2 h i, z ∑ j = 1 V W i, j h j, z ∑ l = 1 K h i, l h j, l ∑ j = 1 V h j, z + 0. 5 β We iteratively updated H according to the updating rule (5) until they satisfied a stopping criterion.

Using ASBC and the above correspondence rule, we obtain a neural tree.

Then, by the chain rule, we obtain α2u ξη + γ2u = β u3.

In these cases, note that when the platforms profile observed is ((x_1,x_2)= AA)), applying Bayes' rule we obtain (hat{q}>1/2).