Pengembangan ekonomi ke arah industri kreatif merupakan salah satu wujud dalam menerima aspirasi mendukung Master plan Percepatan dan Perluasan Pembangunan Ekonomi Indonesia, dengan cita-cita mewujudkan visi Indonesia menjadi negara yang maju. Diantaranya terdapat menuangkan ide gagasan, cita-cita, imajinasi agar menjadikan masyarakat kualitas hidup tinggi sejahtera. mencakup kreatif, diyakini ...

The pruning phase is one of the necessary steps in decision tree induction. Existing pruning algorithms tend to have some or all of the following difficulties: 1) lack of theoretical support; 2) high computational complexity; 3) dependence on validation; 4) complicated implementation. The 2-norm pruning algorithm proposed here addresses all of the above difficulties. This paper demonstrates the...

Most of the land use change modelers have used to model binary land use change rather than multiple land use changes. As a first objective of this study, we compared two well-known LUC models, called classification and regression tree (CART) and artificial neural network (ANN) from two groups of data mining tools, global parametric and local non-parametric models, to model multiple LUCs. The ca...

Univariate decision trees (UDT's) have inherent problems of replication, repetition, and fragmentation. Multivariate decision trees (MDT's) have been proposed to overcome some of the problems. Close examination of the conventional ways of building MDT's, however, reveals that the fragmentation problem still persists. A novel approach is suggested to minimize the fragmentation problem by separat...

vehicle occupants comprise a considerable proportion of traffic crash victims in iran. this paper has focused on vehicleoccupants’ injury severity and employed the classification and regression tree (cart) technique in order toidentify the most important variables affecting the injury severity of these road users in crashes occurred on rural freewaysand multilane highways in iran over a three y...

This paper presents two letter-to-sound (LTS) methods in building a small-footprint multilingual text-to-speech (TTS) engine. For the languages where there exist a systematic relationship between a word format and its pronunciation, we employ a rule-based method. Otherwise, we use a trainingbased method. In the second method, we adopted optimal sequence to implement the process of letter-to-pho...

This paper considers a measure of variable importance frequently used in variable selection methods based on decision trees and tree-based ensemble models, like CART, Random Forests and Gradient Boosting Machine. It is defined as the total heterogeneity reduction produced by a given covariate on the response variable when the sample space is recursively partitioned. Some authors showed that thi...

We present the design and implementation of a custom discrete optimization technique for building rule lists over a categorical feature space. Our algorithm provides the optimal solution, with a certificate of optimality. By leveraging algorithmic bounds, efficient data structures, and computational reuse, we achieve several orders of magnitude speedup in time and a massive reduction of memory ...

Recently, several spectacular bankruptcies, including Fannie Mae, Freddie Mac, Washington Mutual, Merrill Lynch, and Lehman Brothers, have caught the world by surprise. To improve the accuracy of financial distress predictions, this research compares traditional statistical methods (i.e., linear discriminant analysis, logistic regression), decision tree classification methods (i.e., C5.0, CART,...

In this work, we present the induction of a fuzzy model that represents the behavior of a partial known function. We extend the approach of classical induction of a classifier by building a decision tree, and its generalization for regression problems by CART, to build a fuzzy model. It is defined by a collection of fuzzy regions fixed in the input domain of the function. To obtain fuzzy region...