Sentence examples for classification of conditional from inspiring English sources

For the classification of conditional exons from current exon list, we assembled 162,941 unique exons from RefSeq (excluding terminal exons).

For the classification of conditional exons from the current exon list, if we only use the position-specific conservation score, the classification error rate is about 25.2%.

A step-wise approach was used for this analysis, comprising identification of all early benefit assessments of new medicines or new indications during the first 3.5 years after the introduction of the procedure in Germany, identification of the corresponding EPARs/EPAR variations and subsequent classification of data requests in conditional appraisals/PAMs.

In the study [45], protein YER178W was reported to have the phenotype-"Heat sensitivity: increased", which is one kind of "conditional phenotypes" according to the phenotype classification in CYGD.

Naïve Bayes is a simple probabilistic classification algorithm based on Bayes' theorem and has the assumption of conditional independence of the predictive attributes [ 8, 9].

The quality of the classification for that model is high (entropy: 0.805), with no identification problem (condition number: 0.233) and no major violation of conditional independence.

Latent class analysis is a statistical method that allows the classification of individuals into groups based on conditional probabilities [ 30].

Using the Random Forests algorithm, we can classify conditional exons with high specificities (97% for the identification of conditional exons from intron regions and 95% for the classification of known exons) and fair sensitivities (64% and 32% respectively).

Accordingly, the simplified LR can be written as: (3) The assumption of conditional independence, which is also the basis of Naive Bayes classification, may seem to be an oversimplification for many complex real world situations including the current one.

In naive Bayes classification, conditional independence of the feature values f i of feature vector F is assumed.

Probabilistic rules in a classification expert system can result in a sociopathic knowledge base, as a consequence of the assumption of conditional independence between observations and rule modularity.