Data mining is the useful tool to discovering the knowledge from large data. Different methods & algorithms are available in data mining. Classification is most common method used for finding the mine rule from the large database. Decision tree method generally used for the Classification, because it is the simple hierarchical structure for the user understanding & decision making. Various data...

This work focused on re ning the Cognitive Abilities Screening Instrument (CASI) by selecting a clinically signi cant subset of tests, and generating simple and useful models for dementia screening in a cross cultural populace. This is a retrospective study of 57 mild-to-moderately demented patients of African-American, Caucasian, Chinese, Hispanic, and Vietnamese origin and an equal number of ...

We train a decision tree inducer (CART) and a memory-based classifier (MBL) on predicting prosodic pitch accents and breaks in Dutch text, on the basis of shallow, easy-to-compute features. We train the algorithms on both tasks individually and on the two tasks simultaneously. The parameters of both algorithms and the selection of features are optimized per task with iterative deepening, an eff...

This paper builds predictive models of segment duration in context based on the CART models and “additivemultiplicative” models for Korean text-to-speech. It uses a corpus of 670 read sentences collected from one speaker of standard Korean. The best performance was obtained from a CART decision tree model, which shows that the correlation between the observed and the predicted durations is 0.77...

This work focused on re ning the Cognitive Abilities Screening Instrument (CASI) by selecting a clinically signi cant subset of tests, and generating simple and useful models for dementia screening in a cross cultural populace. This is a retrospective study of 57 mild-to-moderately demented patients of African-American, Caucasian, Chinese, Hispanic, and Vietnamese origin and an equal number of ...

Run off resulted from rainfall is the main way of receiving water in most parts of the World. Therefore, prediction of runoff volume resulted from rainfall is getting more and more important in control, harvesting and management of surface water. In this research a number of machine learning and data mining methods including support vector machines, regression trees (CART algorithm), model tree...

panic attacks are discrete episodes of intense fear or discomfort accompanied by symptoms such as palpitations, shortness of breath, sweating, trembling, derealization and a fear of losing control or dying. although panic attacks are required for a diagnosis of panic disorder, they also occur in association with a host of other disorders listed in the 5h version of the diagnostic and statistica...

Decision tree is a data mining technique used for the classification and forecasting of the data. It is the supervised learning algorithm that follows the greedy approach and works in a top down manner. Decision tree uses white box model approach and classifies the data in a hierarchical structure. It makes data easy to represent and understand. It can handle a large database and works well wit...

Early forecasting of project dispute resolutions (PDRs) provides decision-support information for resolving potential procurement problems before a dispute occurs. This study compares the performances of classification and ensemble models for predicting dispute handling methods in public–private partnership (PPP) projects. Model analyses use machine learners (i.e., Support Vector Machines (SVMs...

Neocortical neurones can be classified according to several independent criteria: morphological, physiological, and molecular expression (neuropeptides (NPs) and/or calcium-binding proteins (CaBPs)). While it has been suggested that particular NPs and CaBPs characterize certain anatomical subtypes of neurones, there is also considerable overlap in their expression, and little is known about sim...