the main objective in classification of the nmr spectra of cancerous and healthy tissue , with high number of features is the prerequisites of the minimum number of samples. therefore the use of conventional classifier on this type of the data is not recommended. in the current work, different structures of the artificial neural networks (ann) were tried on classification of different cancerous...

during the time, land cover and as a result land use patterns go through fundamental changes and human factors can have the most important role in this process. knowing these changes could be of great help to the future management of this region. according to this, the main purpose of this study is to monitor the land use-cover changes in the hamedan province area during the three recent decade...

Since the launch of the first land observation satellite Landsat-1 in 1972, many machine learning algorithms have been used to classify pixels in Thematic Mapper (TM) imagery. Classification methods range from parametric supervised classification algorithms such as maximum likelihood, unsupervised algorithms such as ISODAT and k-means clustering to machine learning algorithms such as artificial...

the improvement of high-through-put gene profiling based microarrays technology has provided monitoring the expression value of thousands of genes simultaneously. detailed examination of changes in expression levels of genes can help physicians to have effi cient diagnosing, classification of tumors and cancer’s types as well as effective treatments. finding genes that can classify the group of...

The electrocardiogram (ECG) signal has great importance in diagnosing cardiac arrhythmias. In this paper we have compared three classifiers on the basis of their accuracies for the detection of arrhythmia. The algorithms that are used for classification are supervised machine learning algorithm. The performance of the classifier depends upon its accuracy rate. The classifiers used are Nearest N...