Sentence examples for flexible classifications from inspiring English sources
The use of Cox regression and recursive partitioning did allow for more flexible classifications with more subgroups, leading to a small improvement in discriminative ability and 5-year survival of 34% for the poorest risk patients.
This flexible classification system is able to determine all of the parameters from the training set without any prior knowledge.
For those reasons, the guidance we have provided on this question (Table 1 ) emphasizes the effects of differences (gradients) in these parameters and the effects of those changes rather than a static (less flexible) classification.
To overcome this rigidity, we performed a more flexible classification by hierarchical clustering of 159 patients using the 64-gene set; here the risk score was only used for a description of the resulting clusters.
Our k-mer/taxonomy database supports efficient retrieval of detailed taxonomic information and allows for an exhaustive comparison between competing taxonomic assignments using a novel rank-flexible classification procedure.
Flexible categorization requires continuous monitoring of the changes in the environment to ensure that classification reflects current task demands, even after categories are well learned.
As cancer research develops rapidly, it is essential to ensure highly flexible data classification so that labels do not paralyze the emergence of new concepts.
An initial step defines flexible and logical classifications of environment and disease that can readily translate to causal webs.
Mastitis classification may be improved by going from a strict limit between states to a more flexible and realistic classification.
The evolutional aspects of the case were thus brought out more clearly, by means of more flexible methods of classification, and further links between butterflies and the central problems of nature were provided by biological investigations.
Thus, similarity learning offers a more flexible framework than classification algorithms and can handle problems associated with unbalanced data in a natural way.
