Inductive item tree analysis: Corrections, improvements, and comparisons

Inductive item tree analysis: Corrections, improvements, and comparisons

There are various methods in knowledge space theory for building knowledge structures or surmise relations from data. Few of them have been thoroughly analyzed, making difficult to decide which of these methods provide good results and when to apply each of the methods. In this paper, we investigate the method inductive item tree analysis and discuss the advantages and disadvantages of this alg...

Inductive Corrections of Action Descriptions

In this paper, we show how A-Prolog can be used to perform incremental, inductive learning of the behavior of dynamic domains from (possibly incomplete) observations. The learning module deals with both direct and indirect effects of actions, and is not affected by the frame problem. Moreover, the module can be combined with planning and diagnostic modules, allowing for its integration in auton...

Uncertain Decision Tree Inductive Inference

Induction is the process of reasoning in which General rules are formulated based on limited observations of recurring phenomenal patterns. Decision tree learning is one of the most widely used and practical inductive methods, which represents the results in a tree scheme. Various decision tree algorithms have already been proposed, such as CLS, ID3, Assistant and C4.5. These algorithms suffer ...

Inductive Teaching and Learning Methods : Definitions , Comparisons , and Research Bases

Traditional engineering instruction is deductive, beginning with theories and progressing to the applications of those theories. Alternative teaching approaches are more inductive. Topics are introduced by presenting specific observations, case studies or problems, and theories are taught or the students are helped to discover them only after the need to know them has been established. This stu...

Additions and Corrections