Minimum Support ICA Using Order Statistics. Part I: Quasi-range Based Support Estimation
نویسندگان
چکیده
• v ase s ort esti atio ite i teresti for S I • oice of critical si ce ay lea to ea i less SS sol tio • See artII for ex la atio o o to c oose ive Main References i Minimum Support ICA Using Order Statistics Part I: Quasi-Range Based Support Estimation Frédéric Vrins & Michel Verleysen Université catholique de Louvain – Machine Learning Group www.ucl.ac.be/mlg i i i i i : i i i r ri ri s i l rl s i rsit t li i i r i r .ucl.ac.be/ lg
منابع مشابه
Minimum Support ICA Using Order Statistics. Part II: Performance Analysis
Linear instantaneous independent component analysis (ICA) is a well-known problem, for which efficient algorithms like FastICA and JADE have been developed. Nevertheless, the development of new contrasts and optimization procedures is still needed, e.g. to improve the separation performances in specific cases. For example, algorithms may exploit prior information, such as the sparseness or the ...
متن کاملA Model-Driven Decision Support System for Software Cost Estimation (Case Study: Projects in NASA60 Dataset)
Estimating the costs of software development is one of the most important activities in software project management. Inaccuracies in such estimates may cause irreparable loss. A low estimate of the cost of projects will result in failure on delivery on time and indicates the inefficiency of the software development team. On the other hand, high estimates of resources and costs for a project wil...
متن کاملTumor Classification Using High-Order Gene Expression Profiles Based on Multilinear ICA
Motivation. Independent Components Analysis (ICA) maximizes the statistical independence of the representational components of a training gene expression profiles (GEP) ensemble, but it cannot distinguish relations between the different factors, or different modes, and it is not available to high-order GEP Data Mining. In order to generalize ICA, we introduce Multilinear-ICA and apply it to tum...
متن کاملRobustified distance based fuzzy membership function for support vector machine classification
Fuzzification of support vector machine has been utilized to deal with outlier and noise problem. This importance is achieved, by the means of fuzzy membership function, which is generally built based on the distance of the points to the class centroid. The focus of this research is twofold. Firstly, by taking the advantage of robust statistics in the fuzzy SVM, more emphasis on reducing the im...
متن کاملApplication of Artificial Neural Networks and Support Vector Machines for carbonate pores size estimation from 3D seismic data
This paper proposes a method for the prediction of pore size values in hydrocarbon reservoirs using 3D seismic data. To this end, an actual carbonate oil field in the south-western part ofIranwas selected. Taking real geological conditions into account, different models of reservoir were constructed for a range of viable pore size values. Seismic surveying was performed next on these models. F...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2006