Among the several tasks that evolutionary algorithms have successfully employed, the induction of classification rules and decision trees has been shown to be a relevant approach for several application domains. Decision tree induction algorithms represent one of the most popular techniques for dealing with classification problems. However, conventionally used decision trees induction algorithm...

A new decision tree learning algorithm called IDX is described. More general than existing algorithms, IDX addresses issues of decision tree quality largely overlooked in the artificial intelligence and machine learning literature. Decision tree size, error rate, and expected classification cost are just a few of the quality measures it can exploit. Furthermore, decision trees of varying qualit...

We give a new lower bound on the query complexity of any non-adaptive algorithm for testing whether an unknown Boolean function is a k-junta versus ε-far from every k-junta. Our lower bound is that any non-adaptive algorithm must make Ω ( k log k εc log(log(k)/εc) ) queries for this testing problem, where c is any absolute constant < 1. For suitable values of ε this is asymptotically larger tha...

We report on work towards exible algorithms for solving decision problems represented as in uence diagrams An algorithm is given to construct a tree structure for each decision node in an in uence diagram Each tree represents a decision function and is constructed incrementally The decision maker can balance the cost of comput ing the next incremental improvement to a tree against the expected ...

Certain data is a data whose values are known precisely whereas uncertain data means whose value are not known precisely. But data is always uncertain in real life applications. In data uncertainty attribute value is represented by a set of values. There are two types of attributes in data sets namely, numerical and categorical attributes. Data uncertainty can arise in both numerical and catego...

Improving the precision of heart diseases detection has been investigated by many researchers in the literature. Such improvement induced by the overwhelming health care expenditures and erroneous diagnosis. As a result, various methodologies have been proposed to analyze the disease factors aiming to decrease the physicians practice variation and reduce medical costs and errors. In this paper,...

In this paper we study the problem of how multiple distributed agents can jointly induce a decision tree, such that each of them preserves privacy over its own data and item set and each of them holds a part of the learned tree. Our work is original in the following ways: First of all, we consider agents to maintain data sites and jointly induce a decision tree. This merely reflects reality, as...

the rapid growing of information technology (it) motivates and makes competitive advantages in health care industry. nowadays, many hospitals try to build a successful customer relationship management (crm) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. many hospitals have large data warehouses containing customer ...

the prediction of liquefaction potential of soil due to an earthquake is an essential task in civil engineering. the decision tree is a tree structure consisting of internal and terminal nodes which process the data to ultimately yield a classification. c4.5 is a known algorithm widely used to design decision trees. in this algorithm, a pruning process is carried out to solve the problem of the...

this paper presents a data envelopment analysis (dea) model combined with bootstrapping to assess performance of one of the data mining algorithms. we applied a two-step process for performance productivity analysis of insurance branches within a case study. first, using a dea model, the study analyzes the productivity of eighteen decision-making units (dmus). using a malmquist index, dea deter...