in today’s quality- based competitive world, known as knowledge age, customer attraction is of ultimate importance. in respect to the slogan “customer is always right”, customer relation management is the core of an organizational strategy playing an important role in four aspects of customer identification, customer attraction, customer retaining, and customer satisfaction. commercial organiza...

In this paper, a new decision tree-based clustering technique called Phonetic, Dimensional and State Positional Decision Tree (PDS-DT) is proposed. In PDS-DT, phonetic contexts, dimensions and state positions are grouped simultaneously during decision tree construction. PDS-DT provides a complicate distribution sharing structure without any external control parameters. In speaker-independent co...

In this paper, we present a hardware friendly binary decision tree (DT) classifier for gas identification. The DT classifier is based on an axis-parallel decision tree implemented as threshold networks—one layer of threshold logic units (TLUs) followed by a programmable binary tree implemented using combinational logic circuits. The proposed DT classifier circuit removes the need for multiplica...

This study reports the empirical analysis of a hyper-heuristic evolutionary algorithm that is capable of automatically designing top-down decision-tree induction algorithms. Top-down decision-tree algorithms are of great importance, considering their ability to provide an intuitive and accurate knowledge representation for classification problems. The automatic design of these algorithms seems ...

In the current study, the performances of some decision tree (DT) techniques are evaluated for postearthquake soil liquefaction assessment. A database containing 620 records of seismic parameters and soil properties is used in this study. Three decision tree techniques are used here in two different ways, considering statistical and engineering points of view, to develop decision rules. The DT ...

We give a ln(n) + 1-approximation for the decision tree (DT) problem. We also show that DT does not have a PTAS unless P=NP. An instance of DT is a set of m binary tests T = (T1, . . . , Tm) and a set of n items X = (X1, . . . , Xn). The goal is to output a binary tree where each internal node is a test, each leaf is an item and the average number of tests used to uniquely identify each item (o...

Decision tree Graph-Based Induction (DT-GBI) is proposed that constructs a decision tree for graph structured data. Substructures (patterns) are extracted at each node of a decision tree by stepwise pair expansion (pairwise chunking) in GBI to be used as attributes for testing. Since attributes (features) are constructed while a classifier is being constructed, DT-GBI can be conceived as a meth...

This paper presents a new approach for fault detection and classification in transmission line using Decision Tree (DT). The DT based fault detection algorithm uses 1/4th cycle data of fault currents from fault inception, to generate the optimal decision tree for fault detection. Similarly, the DT based classification algorithm takes half cycle data from fault inception of three phase currents ...

A decision tree is an effective means of data classification from which one can obtain rules that are easy to understand. However, decision trees cannot be conventionally constructed for data which are not explicitly expressed with attribute-value pairs such as graph-structured data. We have proposed a novel algorithm, named Chunkingless Graph-Based Induction (Cl-GBI), for extracting typical pa...

Semantic-based image retrieval has attracted great interest in recent years. This paper proposes a region-based image retrieval system with high-level semantic learning. The key features of the system are: (1) it supports both query by keyword and query by region of interest. The system segments an image into different regions and extracts low-level features of each region. From these features,...