Sentence examples for decision tree classifying from inspiring English sources

In this spirit, our classification procedure begins with the detection of TE features in the consensus sequences, and a decision tree classifying each consensus as a function of these features is then produced (Figure 3).

A decision tree classifies the data by following a path through each node.

The decision tree classified and correctly predicted the input data with an impressive accuracy of 92% in the training set and 71% during cross-validation.

The decision tree classifies a particular pattern through a sequence of questions, beginning at the root node, and formulates the subsequent questions based upon the initial answers.

A decision tree classifies subjects as case or control by sorting them through a tree from node to node where each node is an attribute with a decision rule that guides that subject through different branches of the tree to a leaf that provides its classification.

Most decision tree classifiers are designed to classify the data with categorical or Boolean class labels.

Most decision tree classifiers are designed to classify the objects whose attributes and class labels are single values.

A decision tree classifier model was used to classify the watershed into potentially drained and undrained areas using land cover, soil drainage class, and surface slope data sets.

Cells were then classified as vimentin+or vimentin− using a decision tree classifier.

We trained a bagged decision trees classifier to classify candidate struts using features extracted from the images.

Open image in new window Fig. 20 Initial decision tree for classifying bolt-plates, coal and clutter.