نتایج جستجو برای: feature clustering
تعداد نتایج: 328866 فیلتر نتایج به سال:
Introduction: Clustering of human brain is a very useful tool for diagnosis, treatment, and tracking of brain tumors. There are several methods in this category in order to do this. In this study, modified balanced iterative reducing and clustering using hierarchies (m-BIRCH) was introduced for brain activation clustering. This algorithm has an appropriate speed and good scalability in dealing ...
We study the topic of dimensionality reduction for k-means clustering. Dimensionality reduction encompasses the union of two approaches: 1) feature selection and 2) feature extraction. A feature selection-based algorithm for k-means clustering selects a small subset of the input features and then applies k-means clustering on the selected features. A feature extraction-based algorithm for k-mea...
Text clustering is a critical step in text data analysis and has been extensively studied by the mining community. Most existing algorithms are based on bag-of-words model, which faces high-dimensional sparsity problems ignores structural sequence information. Deep learning-based models such as convolutional neural networks recurrent regard texts sequences but lack supervised signals explainabl...
Dimensionality reduction methods transform or select a low dimensional feature space to efficiently represent the original high dimensional feature space of data. Feature reduction techniques are an important step in many pattern recognition problems in different fields especially in analyzing of high dimensional data. Hyperspectral images are acquired by remote sensors and human face images ar...
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