منابع مشابه
A Projection Clustering Technique Based on Projection
Projection clustering is an important cluster problem. Although there are extensive studies with proposed algorithms and applications, one of the basic computing architectures is that they are all at the level of data objects. The purpose of this paper is to propose a new clustering technique based on grid architecture. Our new technique integrates minimum spanning tree and grid clustering toge...
متن کاملClustering Based on Principal Curve
Clustering algorithms are intensively used in the image analysis field in compression, segmentation, recognition and other tasks. In this work we present a new approach in clustering vector datasets by finding a good order in the set, and then applying an optimal segmentation algorithm. The algorithm heuristically prolongs the optimal scalar quantization technique to vector space. The data set ...
متن کاملTime Series Clustering Ensemble Algorithm Based on Locality Preserving Projection
The time series clustering is one of the important research contents in the time series data mining. Since the dimension of time series is common high, the performance of direct raw time series data clustering is not ideal. How to improve the clustering performance of time series is the main research point of this paper. Firstly, use Locality Preserving Projection (LPP) to time series samples f...
متن کاملLocal Independent Projection Based Classification Using Fuzzy Clustering
In Medical diagnosis, through Magnetic Resonance Images Robustness and accuracy of the Prediction algorithms are very important, because the result is crucial for treatment of Patients. There are many popular classification and clustering algorithms used for predicting the diseases from Images. The goal of clustering a medical image is to simplify the representation of an image into a meaningfu...
متن کاملThe Learning-Curve Sampling Method Applied to Model-Based Clustering
We examine the learning-curve sampling method, an approach for applying machinelearning algorithms to large data sets. The approach is based on the observation that the computational cost of learning a model increases as a function of the sample size of the training data, whereas the accuracy of a model has diminishing improvements as a function of sample size. Thus, the learning-curve sampling...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Statistical Computation and Simulation
سال: 2012
ISSN: 0094-9655,1563-5163
DOI: 10.1080/00949655.2011.572882