Stock prices in each industry are one of the major issues in the stock market. Given the increasing number of shareholders in the stock market and their attention to the price of different stocks in transactions, the prediction of the stock price trend has become significant. Many people use the share price movement process when com-paring different stocks while investing, and also want to pred...

A finite-state method, based on leftmost longestmatch replacement, is presented for segmenting words into graphemes, and for converting graphemes into phonemes. A small set of hand-crafted conversion rules for Dutch achieves a phoneme accuracy of over 93%. The accuracy of the system is further improved by using transformation-based learning. The phoneme accuracy of the best system (using a larg...

This paper propose a semi supervised clustering model TPC-IRBM(Two phase clustering-Integrated rule based model) for clustering large data set such as gene expression data. TPC-IRBM works in two phases to cluster the gene expression data set. The proposed model is based on rule based models CRT,C5,CHAID and QUEST. In the first phase of the model 30 % data(which may vary) is extracted to prepare...

In the first part of the paper we present a short review of applications of digital differential analyzers (DDA) to generation of circles showing that they can be treated as one-step numerical schemes. In the second part we present and discuss a novel fast algorithm based on a two-step numerical scheme (explicit midpoint rule). Although our algorithm is as cheap as the simplest one-step DDA alg...

OBJECTIVES To compare chi-squared automatic interaction detection (CHAID) classification trees vs the seventh edition of the TNM classification for patients with head and neck squamous cell carcinoma and to assess whether CHAID classification trees might improve results obtained with the TNM classification. DESIGN Patient disease was classified according to CHAID classification trees and the ...

The CHAID algorithm has proven to be an effective approach for obtaining a quick but meaningful segmentation where segments are defined in terms of demographic or other variables that are predictive of a single categorical criterion (dependent) variable. However, response data may contain ratings or purchase history on several products, or, in discrete choice experiments, preferences among alte...

This study examined the predictive power of data mining algorithms by comparing the performance of a logistic regression algorithm with that of a decision tree algorithm called CHAID (Chi-squared Automatic Interaction Detection). Unlike in the previous studies, the decision tree performed better than logistic regression. This paper also demonstrated how another data mining model, called associa...

For the sustainable use of groundwater, this study analyzed groundwater productivity-potential using a decision-tree approach in a geographic information system (GIS) in Boryeong and Pohang cities, Korea. The model was based on the relationship between groundwater-productivity data, including specific capacity (SPC), and its related hydrogeological factors. SPC data which is measured and calcul...

BACKGROUND Development of three classification trees (CT) based on the CART (Classification and Regression Trees), CHAID (Chi-Square Automatic Interaction Detection) and C4.5 methodologies for the calculation of probability of hospital mortality; the comparison of the results with the APACHE II, SAPS II and MPM II-24 scores, and with a model based on multiple logistic regression (LR). METHODS...