J. Venna and S. Kaski, "Neighborhood preservation in nonlinear projection methods," in Proceedings of the International Conference on Artificial Neural Networks (ICANN 2001. Home/Search Document Details and Download
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Analysis and Visualization of Gene Expression Data .. - Nikkilä, Törönen, .. (2002) Self-citation (Venna Kaski) (Correct)
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Venna, J., Kaski, S., 2001. Neighborhood preservation in nonlinear projection methods: An experimental study. In: Dor ner, G., Bischof, H., Hornik, K. (Eds.), Arti cial Neural Networks|ICANN 2001. Springer, Berlin, pp. 485{ 491.
Visualized Atlas of a Gene Expression Databank - Venna, Kaski (2005) Self-citation (Venna Kaski) (Correct)
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Jarkko Venna and Samuel Kaski, "Neighborhood preservation in nonlinear projection methods: An experimental study," in Proceedings of ICANN 2001.
Learning More Accurate Metrics for Self-Organizing Maps - Peltonen, Klami, Kaski (2002) (1 citation) Self-citation (Kaski) (Correct)
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Kaski, S., and Venna, J. Neighborhood preservation in nonlinear projection methods: An experimental study. In G. Dor#ner, H. Bischof, and K. Hornik, editors, Artificial Neural Networks--ICANN 2001, 458--491, Springer, Berlin, 2001.
Analysis and Visualization of Gene Expression Data .. - Kaski, Nikkilä.. (2001) (1 citation) Self-citation (Kaski) (Correct)
....to two kinds of traditional methods of data analysis: Dimensionality reduction methods and clustering methods. Projection and multidimensional scaling methods can be used to reduce the dimensionality of the data that can then be visualized in the low dimensional space. According to recent evidence [8] the similarity diagrams formed by the SOM are more trustworthy in the sense that if two data points are close by on the display they are more likely to be close by in the input space as well. Note that it is impossible to construct perfect mappings that reduce dimensionality; di erent methods ....
J. Venna and S. Kaski, \Neighborhood preservation in nonlinear projection methods: An experimental study," in Proc. Int. Conf. on Articial Neural Networks, 2001, submitted.
SOM-Based Exploratory Analysis of Gene Expression Data - Kaski (2001) Self-citation (Kaski) (Correct)
....data samples are closeby on the SOM display then they are close by in the original space as well, at least more often than for alternative methods. This result was obtained empirically by comparing the results of the SOM and traditional multidimensional scaling based non linear projection methods [11]. Such trustworthiness is of course important in data analysis. 3.1 Visualization of Cluster Structures Each data sample, here a gene expression pro le, is mapped onto a certain point on the SOM grid. As a result of the SOM algorithm the data becomes organized on the grid so that close by points ....
J. Venna and S. Kaski. Neighborhood preservation in nonlinear projection methods: An experimental study. In Proceedings of ICANN'01, International Conference on Articial Neural Networks. 2001 Submitted.
Investigation of Alternative Strategies and Quality Measures.. - Dittenbach, al. (2005) (Correct)
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J. Venna and S. Kaski, "Neighborhood preservation in nonlinear projection methods," in Proceedings of the International Conference on Artificial Neural Networks (ICANN 2001.
Icasso: Software For Investigating the Reliability of ICA.. - Himberg, Hyvarinen (2003) (Correct)
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J. Venna and S. Kaski, "Neighborhood preservation in nonlinear projection methods: An experimental study," in Artificial Neural Networks (ICANN 2001.
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