As the computer technology and computer network technology are developing, the amount of data in information industry is getting higher and higher. It is necessary to analyze this large amount of data and extract useful knowledge from it. Process of extracting the useful knowledge from huge set of incomplete, noisy, fuzzy and random data is called data mining. Decision tree classification techn...

Decision Trees are considered to be one of the most popular approaches for representing classifier for various disciplines such as statistics, machine learning and data mining. Classification of Intrusion detection, according to their features into either intrusive or non intrusive class is a widely studied problem. Decision trees are useful to detect intrusion from connection records. In this ...

Variable refrigerant flow (VRF) systems are easily subjected to performance degradation due to refrigerant leakage, mechanical failure or improper maintenance after years of operation. Ideal VRF systems should equip with fault detection and diagnosis (FDD) program to sustain its normal operation. This paper presents the fault diagnosis method for refrigerant charge faults of variable refrigeran...

A hybrid intelligent classiier is built for pattern classiication. It consists of a classiication and regression tree (CART), a genetic algorithm (GA) and a neural network (NN). CART extracts features of the patterns by setting up decision rules. Rule improvement by GA is explored. The rules act as a pre-processing layer of NN, a multi-class neural classiier, through which the most probable cla...

In this paper, we compare three different machine learning techniques for predicting length of stay (LOS) in Pennsylvania Federal and Specialty hospitals. Using the real-world data on 88 hospitals, we compare the performances of three different machine learning techniques—Classification and Regression Tree (CART), Chi-Square Automatic Interaction Detection (CHAID) and Support Vector Regression ...

In this paper, we apply the multinomial logit regression and decision tree approaches to examine the critical deciding factors that affect auditor choice decisions. We first examine the relationship between the auditor choice and firm specific factors. In order to get deeper insights about the association between auditor choice and firm’s characteristics, this paper employs the decision tree ap...

Data mining technology is applied to extract the water supply operation rules in this study. Five characteristic attributes—reservoir storage water, operation period number, water demand, runoff, and hydrological year—are chosen as the dataset, and these characteristic attributes are applied to build a mapping relation with the optimal operation mode calculated by dynamic programming (DP). A Le...

Most existing decision tree systems use a greedy approach to induce trees | locally optimal splits are induced at every node of the tree. Although the greedy approach is suboptimal, it is believed to produce reasonably good trees. In the current work, we attempt to verify this belief. We quantify the goodness of greedy tree induction empirically, using the popular decision tree algorithms, C4.5...

Most existing decision tree systems use a greedy approach to induce trees -locally optimal splits are induced at every node of the tree. Although the greedy approach is suboptimal, it is believed to produce reasonably good trees. In the current work, we attempt to verify this belief. We quantify the goodness of greedy tree induction empirically, using the popular decision tree algorithms, C4.5 ...