Morphological Generation is the task of producing the appropiate inflected form of a lemma in a given textual context and according to some morphological features. This paper describes and evaluates wide-coverage morphological lexicons and a Decision Tree algorithm that perform Morphological Generation in Spanish at state-of-the art level. The Freeling, Leffe and Apertium Spanish lexicons, the ...

Background: An accurate and automatic computer-aided multi-class decision support system to classify the magnetic resonance imaging (MRI) scans of the human brain as normal, Alzheimer, AIDS, cerebral calcinosis, glioma, or metastatic, which helps the radiologists to diagnose the disease in brain MRIs is created. Methods: The performance of the proposed system is validated by using benchmark MRI...

In this work, popular discretization techniques for continuous features in data sets are surveyed, and a new one based on equal width binning and error minimization is introduced. This discretization technique is implemented for the UCI Machine Learning Repository [7] dataset, Adult database and tested on two classifiers from WEKA tool [6], NaiveBayes and J48. Relative performance changes for t...

This research uses four classification algorithms in standard and boosted forms to predict members of a class for an online community. We compare two performance measures, area under the ROC (Receiver Operating Characteristic) curve (AUC) and accuracy in the standard and boosted forms. The research compares four popular algorithms Bayes, logistic regression, J48 and Nearest Neighbor (NN). The a...

Clustering and classification are two important techniques of data mining. Classification is a supervised learning problem of assigning an object to one of several pre-defined categories based upon the attributes of the object. While, clustering is an unsupervised learning problem that group objects based upon distance or similarity. Each group is known as a cluster. In this paper we make use o...

Immobility is an important health concern for the elderly patients and healthcare providers who care for the elderly. The purpose of this study was to test a knowledge discovery method to detect elderly patients with impaired mobility in a large clinical dataset. The research method applied an exploratory design and a data mining classification method (cost sensitive Decision Tree J48 from WEKA...

The nature of clinical data makes it difficult to quickly select, tune and apply machine learning algorithms to clinical prognosis. As a result, a lot of time is spent searching for the most appropriate machine learning algorithms applicable in clinical prognosis that contains either binary-valued or multi-valued attributes. The study set out to identify and evaluate the performance of machine ...

Gear drives are one of the most widely used transmission system in many machinery. Sound signals of a rotating machine contain the dynamic information about its health conditions. Not much information available in the literature reporting suitability of sound signals for fault diagnosis applications. Maximum numbers of literature are based on FFT (Fast Fourier Transform) analysis and have its o...