Sentence examples for mean clustering quality from inspiring English sources
Tukey Post Hoc multiple comparisons test shows that there was a statistically significant difference in the mean clustering quality for the following pairs: DCSTREAM, ConStream and STREAM.
An inspection mean quality of the clusters based on post hoc comparisons using Tukey test indicated that DCSTREAM obtained significantly higher mean in clustering quality than ConStream and STREAM.
In Figure 6, a high cLtlf value means poor cluster quality, because at this level of recursion it is possible to isolate the positive control group in a single cluster and leave few species in isolated groups.
This approach can solve the W-k-means algorithm's problem that the clustering quality is greatly affected by the initial value of weight.
This method can solve the fuzzy C-means algorithm's problem that the clustering quality is greatly affected by the data distributing and the stochastic initializing the centrals of clustering.
Juntunen et al. (2013) applied SOM and k-means clustering for modeling water quality in drinking WTP to assess the essential characteristics of the process.
We have used K-means clustering algorithm to eliminate this compression quality prerequisite.
To identify distinctive process states according to the influent water, four-dimensional raw water quality is classified by k-means clustering.
Esteves et. al studied the use of Mahout k-means clustering on a 1.1GB data set of TCP dumps from an airforce LAN, while examining clustering scalability and quality (Esteves et al. [18]).
