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NB-UVB Phototherapy is one of the most common treatments administrated by dermatologists for psoriasis patients. Although in general, the treatment results in improving the condition, it also can worsen it. If a model can predict the treatment response before hand, the dermatologists can adjust the treatment accordingly. In this paper, we use data mining techniques and conduct four experiments. The...
Neuroscience researchers have a keen interest in finding the connection between various brain regions of an organism. Researchers all across the globe are finding new connections everyday and it is very difficult to keep track of all those, so it is important to create a centralized system which is able to give the relation between brain entities. Databases like PubMed contains abstracts and references...
Extinction profile (EP) is an effective feature extraction method which can well preserve the geometrical characteristics of a hyperspectral image (HSI) and by extracting the EP from first three independent components (ICs) of an HSI, three correlated and complementary groups of EP features can be constructed. In this paper, an EPs fusion (EPs-F) strategy is proposed for HSI classification by exploring...
While state-of-the-art kernels for graphs with discrete labels scale well to graphs with thousands of nodes, the few existing kernels for graphs with continuous attributes, unfortunately, do not scale well. To overcome this limitation, we present hash graph kernels, a general framework to derive kernels for graphs with continuous attributes from discrete ones. The idea is to iteratively turn continuous...
In this paper, the brief survey of data mining classification by using the machine learning techniques is presented. The machine learning techniques like decision tree and support vector machine play the important role in all the applications of artificial intelligence. Decision tree works efficiently with discrete data and SVM is capable of building the nonlinear boundaries among the classes. Both...
Reducing unnecessary lab tests is an essential issue in intensive care unit (ICU). In this paper we analyze lab tests ordered for ICU patients using data mining methods. The selected dataset is extracted from Multi-parameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database. Calcium test is selected as the target test which is one of the frequent tests for gastrointestinal bleeding patients...
In data mining, when using Naive Bayes classification technique, it is necessary to overcome the problem of how to deal with continuous attributes. Most previous work has solved the problem either by using discretization, normal method or kernel method. This study proposes the usage of different continuous probability distribution techniques for Naive Bayes classification. It explores various probability...
Environmental monitoring is one of the key approaches to safeguard the global ecosystem. Classifications of different water levels facilitate in preserving water reserves and maintain the equilibrium in the ecosystem. In this paper we shall inspect the classification of drainage water levels in Canada. A powerful statistical tool called support vector machines is used to classify the said drainage...
Emotions are mental states that can be expressed by motion, speech and other physiological reactions. In human-to-human interaction emotion perception is the perception on the emotion of the other people, which, due to the nature of emotions is not so precise. On the other hand, perception on emotions in human-computer interaction is still an open problem. A lot of work is done in direction of finding...
Revised algorithm for online learning with kernels (OLK) in classification and regression is proposed in a reproducing kernel hilbert space (RKHS). Compared with the original OLK, the revised algorithm allows that the new data points arrive either one by one or two by two.
Opinion mining is a challenging task to identify the opinions or sentiments underlying user generated contents, such as online product reviews, blogs, discussion forums, etc. Previous studies that adopt machine learning algorithms mainly focus on designing effective features for this complex task. This paper presents our approach based on tree kernels for opinion mining of online product reviews....
Graph classification is important for different scientific applications; it can be exploited in various problems related to bioinformatics and cheminformatics. Given their graphs, there is increasing need for classifying small molecules to predict their properties such as activity, toxicity or mutagenicity. Using subtrees as feature set for graph classification in kernel methods has been shown to...
For multi-label classification, problem transform algorithms have received more attention due to their good performance and low computational complexity. But how to speed up training and test procedures is still a challenging issue. In this paper, one-by-one data decomposition trick is adopted to divide a k-label problem into k sub-problems, where a specific sub-problem only consists of instances...
In this paper, an evolutionary hybrid approach is studied for fault diagnosis and it is applied to classify the loopers faults in hot rolling process. The algorithm called evolutionary KPCA-LSSVM is the combination of genetic algorithm (GA), kernel principal component analysis (KPCA) and Least Squares Support Vector Machine (LSSVM), which can obtain better fault recognition rate. Firstly, kernel function...
In recent years high-resolution space borne images have disclosed a large number of new opportunities for medium and large-scale rubber plant mapping. Some traditional algorithms used for hyper spectral remote sensing image classification have some problems such as low computing rate, low accuracy. According to SVM theory, the Rubber plant classification model based on SVM was constructed, by experimenting...
Extracting knowledge out of qualitative data is an ever-growing issue in our networking world. Opposite to the widespread trend consisting of extending general classification methods to zero/one-valued qualitative variables, we explore here another path: we first build a specific representation for these data, respectful of the non-occurrence as well as presence of an item, and making the interactions...
This paper describes an efficient way to presort students as possible pass / fail courses in which use of distance education as an aid or fully in its activities. The environment was used moodle and technique of data mining for classification was the SVM (Support Vector Machine). This makes it possible to efficiently classify the chance to be a student flunking a course and then act in a preventative...
In this paper, two independent support vector machines were connected to a paraconsistent logic unit in order to establish a new classification scheme which takes into account the degrees of faith and uncertainty of a certain statement. By using this approach, one can classify an input signal as matching one of two independent classes or both of them. In our experiments, speech data constitute the...
City scientific and technological progress level classification and promotion play a central role in spurring city income growth and reducing poverty. Based on the Chinese city data availability, this paper built evaluation index system on the level of city scientific and technological progress. According to the city scientific and technological progress data which is large scale and imbalance, this...
Recent advances in the power and resolution capabilities of MR scanners have extended the reach of magnetic resonance spectroscopy as a powerful non-invasive diagnostic tool. Coupled with MRI techniques it can provide accurate identification and quantification of biologically important compounds in soft tissue. In practice sensor calibration issues, magnetic field homogeneity effects and measurement...
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