background non-alcoholic fatty liver disease (nafld) is the most common form of liver disease in many parts of the world. objectives the aim of the present study was to identify the most important factors influencing nafld using a classification tree (ct) to predict the probability of nafld. patients and methods this cross-sectional study was conducted in kavar, a town in the south of fars prov...

using satellite imagery for the study of earth's resources is attended by manyresearchers. in fact, the various phenomena have different spectral response inelectromagnetic radiation. one major application of satellite data is the classification ofland cover. in recent years, a number of classification algorithms have been developed forclassification of remote sensing data. one of the most nota...

decision-tree algorithms provide one of the most popular methodologies for symbolic knowledge acquisition. the resulting knowledge, a symbolic decision tree along with a simple inference mechanism, has been praised for comprehensibility. the most comprehensible decision trees have been designed for perfect symbolic data. classical crisp decision trees (dt) are widely applied to classification t...

the classification and regression trees (cart) possess the advantage of being able to handlelarge data sets and yield readily interpretable models. in spite to these advantages, they are alsorecognized as highly unstable classifiers with respect to minor perturbations in the training data.in the other words methods present high variance. fuzzy logic brings in an improvement in theseaspects due ...

forest types mapping, is one of the most necessary elements in the forest management and silviculture treatments. traditional methods such as field surveys are almost time-consuming and cost-intensive. improvements in remote sensing data sources and classification –estimation methods are preparing new opportunities for obtaining more accurate forest biophysical attributes maps. this research co...

in this paper, first, an initial feature vector for vocal fold pathology diagnosis is proposed. then, for optimizing the initial feature vector, a genetic algorithm is proposed. some experiments are carried out for evaluating and comparing the classification accuracies which are obtained by the use of the different classifiers (ensemble of decision tree, discriminant analysis and k-nearest neig...

In this paper, first, an initial feature vector for vocal fold pathology diagnosis is proposed. Then, for optimizing the initial feature vector, a genetic algorithm is proposed. Some experiments are carried out for evaluating and comparing the classification accuracies which are obtained by the use of the different classifiers (ensemble of decision tree, discriminant analysis and K-nearest neig...