The precision is the proportion of the examples that are truly positive class among all those which were classified as positive class.
The tuning selects the value of Δ that maximizes TP + TN, with TP the true positive rate and TN the proportion of negative examples that are correctly classified.
Although quantitative DNA FCM analysis can accurately detect and quantify DNA aneuploid cell populations, it cannot delineate the proportion of, for example, diploid cancer cells versus diploid non-tumor cells.
Similarly to the work of [31], in our research we also consider the question of what is the appropriate proportion of examples of each class (benign and malicious) for learning if only a limited number of training instances can be used altogether.
Given two classes "positive" and "negative", TP rate is the proportion of correctly predicted positive examples, and FP rate is the proportion of negative examples that are incorrectly predicted positive.
The specificity is the proportion of true negatives among all examples that are negative class.
Yet, in all three examples the proportion of false positive genes decreased with more stringent thresholds both above and below the reference cut-off.
Since 2008, for example, the proportion of people working on temporary and zero-hours contracts has increased greatly.
In the past 18 years, for example, the proportion of privately educated high court judges has barely shifted: in 1989, it was 74%; in 2007, it was 70%.
As one stark example, the proportion of Stanford M.B.A.'s taking jobs with either consulting firms or investment banks dropped to 33percentt last year from 43percentt in 1998.
