The Mahalanobis distance [41] is used in a classification procedure to measure the distance of the feature vector of an object to the centroid of each class.
Using a classification and regression tree (CART) procedure to analyse simulation output, we explored the dynamics of multiple strategies in concert.
The recognition process involves two steps: first step is feature extraction using shape based features, and the second one is a classification procedure using ANN through a back propagation algorithm.
The centroid prediction of tumor samples to specific subtypes as described above represents a classification procedure, using Norway/Stanford data as the training set; that is, we forced the samples to fit into one of five prespecified categories.
Next, a classification procedure uses those vectors to differentiate between genres.
We used a multivariate classification procedure to characterize the temporal dynamics of information processing when the stimulus was perceived consciously vs unconsciously.
To evaluate potential markers for PZ and TZ tissues a classification procedure was performed using the ADTree algorithm, which generates trees where each decision node specifies a miRNA and a threshold expression value, while the prediction nodes contain numbers, which are summed up when the classification is done.
Since the composition of our dataset was significantly enriched for triple-negative breast cancers, therefore deviating from the original data set composition used to develop PAM50 centroids, we used an iterative classification procedure based on random sampling, as described in [ 10]. miRNA data were pre-processed using the AgiMicroRna (http://www.aroma-project.org) R package [ 47].
The maximum likelihood classifier (threshold level of 0.95, i.e. 95%) was also adopted, a widely used classification procedure of digital remotely sensed data (Foody et al. 1995), and it takes the variability of classes into account by using the covariance matrices of classes (Schriever and Congalton 1995).
Plots were classified on the basis of herbaceous species cover using the TWINSPAN classification procedure.
