Selected article for: "additional information and logistic model"
Author: Phillip Davis; John Bagnoli; David Yarmosh; Alan Shteyman; Lance Presser; Sharon Altmann; Shelton Bradrick; Joseph A. Russell
Title: Vorpal: A novel RNA virus feature-extraction algorithm demonstrated through interpretable genotype-to-phenotype linear models
  • Document date: 2020_3_2
    • ID: 48mtdwuv_22
    Snippet: The fragility of the phenotype for the Influenza A model resulted in a model with higher 287 complexity than the other RNA viruses studied. However, this provides another avenue for 288 model analysis. Logistic regression classifiers offer not only an output label, but also a 289 probability assignment to the corresponding label. Thus, additional information can be encoded 290 in this output. Figure 5 presents a graphical representation of the di.....
    Document: The fragility of the phenotype for the Influenza A model resulted in a model with higher 287 complexity than the other RNA viruses studied. However, this provides another avenue for 288 model analysis. Logistic regression classifiers offer not only an output label, but also a 289 probability assignment to the corresponding label. Thus, additional information can be encoded 290 in this output. Figure 5 presents a graphical representation of the distribution of these class 291 probabilities for the training sets for the segments described.

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