Sentence examples for incremental selection from inspiring English sources

In order to find the εR(i), simple incremental selection algorithm [50] is used.

Some algorithms that avoid serial searches and with optimal performance have been proposed, we call those the incremental selection and the decremental selection.

The incremental selection AST (I-AST) adds successively antennas at every stage, so the antenna that yields the maximum increase of the channel capacity is added to the set of P transmit antennas [14].

In [10] and [11], the authors proposed incremental selection AF relaying schemes, in which the source retransmits its signal when doubling the received SNR in the SD link satisfies the target SNR.

This estimated complexity for optimal selection can be deemed as an upper bound of the complexity of any hybrid AS scheme, since there exist some suboptimal but reduced complexity algorithms, such as the incremental selection and the decremental selection algorithms in [7].

Ultimately, we are proposing the Darwinian metaphor to facilitate alternative ways of thinking that allows a greater emphasis on the importance of implementation strategies (not just policy), evaluation of implementation strategies, and incremental selection of advantageous strategies that, over time, cumulatively, and adapted to the local context, may assist in strengthening health systems.

Meanwhile, the Incremental Feature Selection and Forward Feature Selection are applied for feature selection.

After adopting Minimum Redundancy Maximum Relevance and Incremental Feature Selection as the feature selection techniques and random forest as the classification model, 55 optimal features were obtained, with which the classification model achieved the best performance.

The Maximum Relevance Minimum Redundancy (mRMR) method combining with Incremental Feature Selection (IFS) and Feature Forward Selection (FFS) are then applied for feature selection.

The one that can achieve the highest prediction accuracy or smallest log rank test p-value is considered to be the optimized feature set selected by Incremental Feature Selection (IFS) [14], [15], [19].

More specifically, to identify the most important features regulating translation rates under different conditions, we applied maximum relevance & minimum redundancy and incremental feature selection to select the important features for predicting the translation rate in rich and starvation conditions, respectively.