Titlebook: Machine Learning and Data Mining in Pattern Recognition; 12th International C Petra Perner Conference proceedings 2016 Springer Internation

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abracadabra

Evolving a Low Price Recovery Strategy for Distressed Securities,e selection and extraction, design of various genetic programs for evolving the agent, and testing approaches for the agents. We demonstrate that the evolved agent yields results outperform a randomized version of the LPRS and the benchmark Standard & Poor’s 500 (S&P500) stock market index.

生来

A Spectral Clustering Based Outlier Detection Technique,s by using the information of eigenvalues and eigenvectors statistically in the feature space. We compare the performance of our methods with distance-based outlier detection methods and density-based outlier detection methods. Experimental results show the effectiveness of our algorithm for identif

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Insubordinate

Using Support Vector Machines for Intelligent Service Agents Decision Making,s to create the normal model and compared their overall performance together as well as the benchmark, that is, rational web services without learning abilities. The results show that the Gaussian kernel outperforms the other two learning models as well as the benchmark non-learning model by maintai

商议

K-Means over Incomplete Datasets Using Mean Euclidean Distance,s the centroid is computed. Even so, the runtime complexity of the suggested k-means is the same as the standard k-means over complete datasets. We experimented on six standard numerical datasets from different fields and compared the performance of our proposed k-means to other basic methods. Our e

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小木槌

Automatic Detection of Latent Common Clusters of Groups in MultiGroup Regression, prior. This spares the model from needing to memorize the entire data of previous groups. The posterior inference for iMG-GLM-1 is done using Variational Inference and that for iMG-GLM-2 using a simple Metropolis Hastings Algorithm. We demonstrate iMG-GLM’s superior accuracy in comparison to well k

foliage

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