Your English writing platform
Discover LudwigExact(17)
In particular, we present a coalition formation algorithm inspired by the well known class of hierarchical agglomerative clustering techniques (Linkage algorithms).
This paper uses control theory to gain insight into these numerical instabilities as well as to design linkage algorithms that modify the dynamic information passed between the individual codes to numerically stabilize their coupling, and to increase the numerical accuracy of the simulation results.
Linkage algorithms were implemented as SQL server stored procedures.
RS directed the SAFELINK-project on record linkage algorithms.
Clustering trees were constructed using average linkage algorithms and Pearson's correlation.
Correlation (centred) similarity matrix and average linkage algorithms were used in the cluster analysis.
Similar(43)
Clusters were built using a similarity threshold of 0.7 with a complete linkage algorithm.
For the hierarchical methods the ward linkage algorithm performs best under our simulation design.
We also compare the proposed technique with three function-level clustering techniques Single Linkage algorithm (SLINK), Complete Linkage algorithm (CLINK) and Weighted Pair-Group Method using Arithmetic averages (WPGMA).
Here, we use a simple elimination method to remove extra solutions from the archive instead of single linkage algorithm and avoid its complexity.
Hierarchical clustering was performed using a centroid linkage algorithm with an uncentered Pearson correlation similarity metric.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com