… regarding the test costs during the test cost sensitive attribute reduction process, we propose
an … into the test cost sensitive decision model and establish a basis for quantitative analysis. …

… costs such as the attribute cost (eg, the diagnostic test cost) and the misclassification cost
(eg, the false negative test cost). They show that the diagnostic tests and the misclassification …

… Usually the cost for the sequence of testing is denoted as test cost, while the cost of delaying
action on a decision is denoted as delay cost. Table 4 offers an example of delay costs. …

… cost-sensitive learning. In this paper, we propose a cost-sensitive hierarchical classification
… sensitive weights accordingly. First, we use the class hierarchy to divide a large hierarchical …

… Forest classification and introduce a completely new feature selection idea. Additionally,
we also develop cost-sensitive adaptations for existing popular methods in this context. …

… requirement, α, increases with the test cost, c0. Therefore, to … This paper proposes a
quantitative model for estimating the … bounds for accuracy through quantitative analysis. Firstly, for …

… This approach is often referred to as cost-based feature selection or Test-cost-sensitive
Feature Selection (TCSFS). For instance, Min et al. (2011) proposed an information gain-based …

… conducted that synthesized the qualitative research evidence on end-… A qualitative coding
framework was developed from the … End-user values and preferences Qualitative data from the …

… dual-measurement points for quantitative interpretation in managed pressure drilling. …
problem, cost-sensitive learning is introduced. Cost-sensitive learning trains a classifier under the …

… A threshold analyses on GIFT's sensitivity revealed that the strategy would remain the
most cost-effective unless the sensitivity of the test assay decreased below 14.83%. From the …