… decision tree for TS consists of a decision node identifying the test and one branch for each
possible outcome. The same tree-… ith branch leads to the decision tree constructed from the …

… , a decision tree makes decisions based on tree structures, which is also a common decision-…
we usually go through a series of judgments or sub-decisions: we first consider What is the …

… The tree on previous slide is a Boolean decision tree: ✔ the decision is a binary variable (true,
false), and … How to build a decision tree discriminating the 2 robot classes? …

… Then, we load the R decision tree library and grow an unconstrained decision tree.
Specifically, we allow the leaf nodes to contain at least one sample, and internal nodes to have at …

Decision Trees (DTs) are predictive models in supervised learning, known not only for their
unquestionable utility in a wide range of applications but also for their interpretability and …

… Decision Tree This case study considers the decision tree shown in Figure 5, taken from [50,
Ch. 07,page 298]. The example consists in predicting whether a person reads an article …

… consider sequential decision problems with uncertainty, represented as decision trees.
Sensitivity analysis is always a crucial element of decision making and in decision trees it often …

… tree model. We also introduce a novel way to visualize the subgroups defined by decision
trees. … scientifically meaningful characterization of the subgroups identified by decision trees. …

… a decision tree might … decisions, decision trees are much easier to be explained in human
languages. Although conventionally, decision trees are used for supporting Boolean decisions…

… decision tree algorithms are often greedy or myopic, and sometimes produce unquestionably
suboptimal models. Hardness of decision tree … for optimal decision trees for binary variables…