"bipartite classification" is a correct and usable phrase in written English.
It refers to a type of classification or organization that divides things into two distinct parts or categories. Example: "The study used a bipartite classification system to categorize the data into two groups based on demographic factors."
This bipartite classification has been challenged by the recent discovery of new deeply branching lineages (e.g., Thaumarchaeota, Aigarchaeota, Nanoarchaeota, Korarchaeota, Parvarchaeota, Aenigmarchaeota, Diapherotrites, and Nanohaloarchaeota) which have also been given the same taxonomic status of kingdoms.
The analysis presented here allows us to examine, out of academic interest, what the classification of bipartite begomoviruses would be if it were based solely on the DNA-B component (Table 2).
It represents disease disease associations in terms of bipartite graphs and provides International Classification of Diseases, Ninth Revision (ICD9 -centric and dICD9 -centricentric views of diseand information.
With a different idea of regarding similarity matrices of drugs and targets as kernel matrices, kernel-based techniques of classification, such as bipartite local model (BLM) [ 8– 10], are also popularly applied to DTI prediction.
To compare both unipartite and bipartite partitions with the external article classification, we will be focussed only on the articles that fall into each cluster.
The reported values of normalized mutual information indicate the existence of some common information between automatically identified clusters of articles (both in the bipartite and unipartite cases) and the author based classification.
Each method formulates the task as one of text classification, models the data as a bipartite graph of documents and words, and enables prior knowledge concerning the sentiment orientation of documents or words of interest to be effectively combined with "auxiliary" information to produce accurate sentiment estimates.
Each method formulates the task as one of text classification, models the data as a bipartite graph of documents and words, and assumes that only limited prior information is available regarding the sentiment orientation of any of the documents or words of interest.
The analyses of bipartite begomovirus component sequences indicate that our present classification system, based entirely on their DNA-A components, holds for the majority of viruses were the system instead to be based on DNA-B components; the exceptions to this being the cases where pseudo-recombination has occurred.
ApicoAP [ 6] is a generalized rule-based classification model that identifies apicoplast-targeted proteins that use a bipartite signaling mechanism (ApicoTPs).
This observation motivates us to propose a Spectral Feature Alignment (SFA) based method to align workflow DS templates from different domains in a latent space by modeling the correlation between the DI and DS workflow templates in a bipartite graph and using DS features as a bridge for cross-domain Big Data classification.
