Examples of using Decision trees in English and their translations into Russian
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Colloquial
combining of regression and decision trees.
Decision trees are widely used to help make good choices in many different disciplines including medical diagnosis,
Pruning is a technique in machine learning that reduces the size of decision trees by removing sections of the tree that provide little power to classify instances.
logistic regression, decision trees, and other data mining models.
can be used to produce a stronger ensemble than very deliberate algorithms like entropy-reducing decision trees.
notably naive Bayes classifiers, decision trees and boosting methods,
As an example, the random forest algorithm combines random decision trees with bagging to achieve very high classification accuracy.
although they are occasionally erroneously mistaken for flowcharts or directed decision trees.
This can be achieved by reviewing the decision trees(Annex 2)
Decision trees and other methodological tools,
For data including categorical variables with different numbers of levels, information gain in decision trees is biased in favor of attributes with more levels.
Decision trees are decision support tools that use a tree-like graph
Decision trees provide analytical frameworks that facilitate discussion
While decision trees help shape the discussion on a given subsidy scheme,
The decision trees in sub-sections 2.2.x.3(list of collective entries) at the end
partially ordered sets, decision trees, necklace problems
such as a collection of individual stack-size-based starting hand tables, decision trees or heads-up displays that dynamically change based on actions,
IBM SPSS Decision Trees, IBM SPSS Direct Marketing,
Decision trees and other methodological tools,
Decision trees and other methodological tools,
