Sentence examples for estimated classification from inspiring English sources

In Figure 7 we visualize linear projections of the testing data as well as the estimated classification boundaries.

They consider the classification error as a criterion for extracting features and an iterative gradient descent algorithm is utilized to minimize the estimated classification error.

Table 5 displays the top-ten 1-gene, 2-gene and 3-gene classifiers, respectively, ranked by estimated classification error.

Additionally, we report the estimated classification rates as follows: <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0003475.e032.PNG" class= inline-graphic"/> where εij = inline-graphicP classification = j|true CNP classification = i).

To avoid the weakness of filtering methods, wrapper methods wrap around a particular learning algorithm that can assess the selected feature subsets in terms of the estimated classification errors and then build the final classifier [13].

We estimated classification performance and interpret the obtained importance maps at a single-subject level for three stimulus modalities: auditory (an object's spoken name), visual (a drawing of an object), and orthographic (an object's written name).

To estimate classification performance in the validation data sets we again performed LOOCV.

LOOCV is also used to estimate classification accuracy, as reported in Figure 1B.

We applied consensus clustering [ 36], a resampling-based method to estimate classification stability and classification accuracy (See Methods for details).

To accurately estimate classification rates, gene re-sampling was performed during each round of cross-validation [ 20].

This design divides the collection into a training set and a test set as a means of estimating classification accuracy.