Titlebook: Non-Standard Parameter Adaptation for Exploratory Data Analysis; Wesam Ashour Barbakh,Ying Wu,Colin Fyfe Book 2009 Springer-Verlag Berlin

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Connectivity Graphs and Clustering with Similarity Functions,s between data points. In this section we review two popular methods to construct a similarity graph, and then we introduce a new algorithm that solves some problems that can not be solved by the others.

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1860-949X earch in Reinforcement learning, cross entropy and artificia.Exploratory data analysis, also known as data mining or knowledge discovery from databases, is typically based on the optimisation of a specific function of a dataset. Such optimisation is often performed with gradient descent or variation

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Introduction,to compute probabilities and quantiles for the distribution of annual rainfall, assumed to be normally distributed, in a region. The more data there is available, the more accurate an answer can be given. However, it is extremely difficult to investigate the structure of a data set that is high dime

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Online Clustering Algorithms and Reinforcement Learning,totypes to learn in a different way, online, to that in batch mode. This may lead to different results due to the different behavior in the learning process. Furthermore, a limitation of batch processing algorithms is that they cannot readily respond to new data if the data only becomes available ov

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