کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
532394 869947 2012 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Cohort-based kernel visualisation with scatter matrices
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Cohort-based kernel visualisation with scatter matrices
چکیده انگلیسی

Visualisation with good discrimination between data cohorts is important for exploratory data analysis and for decision support interfaces. This paper proposes a kernel extension of the cluster-based linear visualisation method described in Lisboa et al. [15]. A representation of the data in dual form permits the application of the kernel trick, so projecting the data onto the orthonormalised cohort means in the feature space. The only parameters of the method are those for the kernel function. The method is shown to obtain well-discriminating visualisations of non-linearly separable data with low computational cost. The linearity of the visualisation was tested using nearest neighbour and linear discriminant classifiers, achieving significant improvements in classification accuracy with respect to the original features, especially for high-dimensional data, where 93% accuracy was obtained for the Splice-junction Gene Sequences data set from the UCI repository.


► Visualisation with good discrimination between data cohorts.
► Kernel extension of the cluster-based linear method described in Lisboa et al. [15].
► The only parameters of the method are those for the kernel function.
► Obtains well-discriminating visualisations of non-linearly separable data.
► Low computational cost.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 45, Issue 4, April 2012, Pages 1436–1454
نویسندگان
, , ,