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Nonetheless, it works on any data set, independent of the data transformation methods used [31].
Two data transformation methods were utilised with only markers that were significant in both selected for further analysis.
When dealing with heterogenous experimental datasets from different laboratories and experimental settings, efficient data transformation methods are necessary to produce a reasonable level of comparability.
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To propose a new consistent data transformation method in spatial domain, this paper applies the PCA transform to the spatial information of the neighboring pixels.
Clustering is another utilized data transformation method.
With special focus on network clustering, our study addresses this open question by proposing a data transformation method and a clustering framework.
First, they proposed a data transformation method to construct an easily consumable input form (the statistical feature matrix) from raw GPS time series for deep learning.
Spatialization is defined as a data transformation method based on spatial metaphors, with the aim of generating a cognitively adequate graphic representation for data exploration and knowledge discovery in multi-dimensional databases.
Moreover a data transformation method induced by the orthogonal motion of machine tools is proposed to obtain the three-dimensional trajectory in the machine tool coordinate frame and the contouring error can be calculated.
Another data transformation method frequently applied in gene expression studies is the binary transformation [ 18].
We are, therefore, not reliant on the suitability of the data transformation method chosen.
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