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At the Network Layer, well known approaches to aggregation include the Shortest Path Tree (SPT), wherein a single, network-wide aggregation tree is centrally calculated and configured and the Greedy Incremental Tree (GIT) which approximates a shortest path tree, but is constructed in an incremental and decentralised fashion [25].
Next, to learn the driver's preferences in multi-criteria route selection and to classify any route based on these preferences, a methodology was proposed using a locally linear neuro-fuzzy model (LLNFM) trained with an incremental tree based learning algorithm.
The greedy incremental tree (GIT)[20] is a heuristic strategy of building an aggregation tree so that the number of packet transmission is minimized.
Intanagonwiwat et al. [11] proposed greedy incremental tree which establishes an energy-efficient tree by attaching all sensors greedily onto an energy-efficient path and prunes less energy-efficient paths.
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Incremental decision tree (hoffding tree or VFDT) uses a statistic result (hoffding bounds) to guaranteeing that we can learn from abundant data within practical time and memory constraints.
Incremental decision tree and Incremental Bayesian algorithm is faster and Incremental SVM algorithm has better a generalization ability.
In these three algorithms, Incremental decision tree and Incremental Bayesian algorithms are based on experience risk minimization.
CBD's generalization accuracy is compared with that of C4.5, C4.5 with rules, incremental decision trees, oblique classifiers, linear machine decision trees, CN2, learning vector quantization (LVQ), backpropagation, nearest neighbor, Q* and radial basis functions (RBFs).
This iterative seed extension method yields similar results to incremental suffix-tree or Burrows-Wheeler mapping but with dramatically fewer index memory accesses, which is critical to DRAGEN's mapping speed.
We also show how to efficiently generate a class of incremental random game trees.
It creates – in incremental manner – hierarchical, tree-like structure, adapting it to the specific problem being solved.
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