Introduction: In this paper, a method is presented to classify the breast cancer masses according to new geometric features. Methods: After obtaining digital breast mammogram images from the digital database for screening mammography (DDSM), image preprocessing was performed. Then, by using image processing methods, an algorithm was developed for automatic extracting of masses from other norma...

reservoir permeability is a critical parameter for characterization of the hydrocarbon reservoirs. in fact, determination of permeability is a crucial task in reserve estimation, production and development. traditional methods for permeability prediction are well log and core data analysis which are very expensive and time-consuming. well log data is an alternative approach for prediction of pe...

Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of machine learning. In this paper we have used an approach by using support vector machine classifier to construct a model that is useful for the breast cancer survivability prediction. We have used both 5 cross and 10 cross validation of variable selection on input feature vectors and the perfo...

In this work, a Genetic Algorithm boosted Least Square Support Vector Machine model by a set of linear equations instead of a quadratic program, which is improved version of Support Vector Machine model, was used for estimation of 98 pure compounds second virial coefficient. Compounds were classified to the different groups. Finest parameters were obtained by Genetic Algorithm method ...

Several combinations of the preprocessing algorithms, feature selection techniques and classifiers can be applied to the data classification tasks. This study introduces a new accurate classifier, the proposed classifier consist from four components: Signal-toNoise as a feature selection technique, support vector machine, Bayesian neural network and AdaBoost as an ensemble algorithm. To verify ...

We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, we find that standard machine learning techniques definitively outperform human-produced baselines. However, the three machine learning methods we employed (Naive Bayes, maximum entropy classification, and support vecto...

ultrasound imaging is a popular and noninvasive tool frequently used in the diagnoses of liver diseases. a system to characterize normal,fatty and heterogeneous liver, using textural analysis of liver ultrasound images, is proposed in this paper. the proposed approach isable to select the optimum regions of interest of the liver images. these optimum regions of interests are analyzed by two lev...

This paper presents a strategy of adaptive online sketchy shape recognition. The inputting sketchy shapes are recognized online by means of a modified Support Vector Machine (SVM) incremental learning classifier. All classified results evaluated by user are collected and some important samples are selected according to their distances to the hyper-plane of the SVM-classifier. The classifier can...

Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment ana...