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The multifaceted approach adapts classical TSP heuristics by means of instance-partitioning and sampling, and may be of independent interest.
Leave-One-Out Cross-Validation (LOOCV) is applied to validate the feature rankings by subdividing the dataset into m (m = the number of instances) partitions.
The distributions of instances per partition are displayed in Figure 7 following the three degrees per dimension.
However, in both instances, the partition distance is identical.
In the clustering process, the instances are partitioned into clusters based on their similarity.
The attribute with the highest information gain is chosen as the attribute for the current node, and the instances are partitioned accordingly.
The 40,000 sampled instances were partitioned into eight bins according to the RF distance observed between the BIONJ-GTR tree and the true (LTP) tree, and average RF distances were recorded for each of the three SR functions in each bin.
For instance, a lattice partition chain is visualized in Figure 3 for the two-dimensional case.
The Generalized Finite Element Method (GFEM) is a meshbased approach that can be considered as one instance of the Partition of Unity Method (PUM).
For instance, when we partition a specific region and consider it as a reconfigurable part, some static interfacing might go through the reconfigurable part or some static logic (e.g., control logic) might exist in the partitioned region.
Instances in a partition will store data of the same key range or they are replications of each other.
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