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One can use information about shorter solid lines to extract information about how data is clustered in a similar way as with linkage-clustering methods [3].
User data is clustered on the server side using default parameters.
Firstly, the input-output data is clustered according to the subtractive clustering method.
In this method, the input of price data is clustered by TS fuzzy model.
Next, we design the clustered groups algorithm (CGA), which accelerates top-k groups processing for the case where data is clustered by a subset of group-by attributes.
After the fuzzy data is clustered into marketing segments, the centre points of market segments are used as ideal points for new product development.
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The most common approach for detecting functionally related gene sets from such high throughput data is clustering [ 1].
In the clustering step, the training data was clustered into n clusters using K-means algorithm [34].
Transcriptome data were clustered using weighted gene coexpression network analysis (WGCNA), a tailored method for identification of highly coexpressed gene sets23.
Based on the wavelet coefficients of the final approximation, the GWL data was clustered into three groups (WCG1 to WCG3).
Data are clustered at daily averaged resolution; in total, we classified six categories, five of which clearly describe the ultrafine aerosol population, one of which is linked to nucleation events (up to 39% during summer).
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CEO of Professional Science Editing for Scientists @ prosciediting.com