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Clustering analysis is an active research branch in the area of data mining due to its simplicity and rapidity. However, K-means algorithm has the shortcomings of heavily depending on the initial clustering center and easily falls into local optimum. In this paper, we consider a deep research on K-means algorithm of optimization. We put forward the first selected initial clustering center of K-means...
Fruit fly optimization algorithm (FOA) is a new method for finding global optimization based on food finding behavior of the fruit fly. The original FOA can only solve problems that have optimal solutions in zero vicinity. To make FOA more universal for the continuous optimization problems, especially for those problems with optimal solution that are not zero. This paper proposes a hybrid fruit fly...
The popular fuzzy c-means algorithm (FCM) is an objective function based clustering method. Hence, different objective function may lead to different results. The important issue is how to get a more compact and separable objective function to improve the cluster accuracy. The objective function of the well known improved algorithm, FCS, is a generalization of the FCM objective function by combining...
In search of good prediction algorithm of thermostable proteins is an important issue. In this paper, a novel prediction algorithm of thermostable proteins by using Hurst exponent and Choquet integral regression model based on lambda-measure and gamma-support is proposed. This method not used before is the first one integrating the physicochemical properties, fractal property and Choquet integral...
Two well known fuzzy partition clustering algorithms, FCM and FPCM are based on Euclidean distance function, which can only be used to detect spherical structural clusters. GK clustering algorithm and GG clustering algorithm, were developed to detect non-spherical structural clusters, but both of them fail to consider the relationships between cluster centers in the objective function, needing additional...
The support vector machine (SVM) classifier is a popular and appealing classifier .It could be improved by taking some transformation about the original data before classification even sometimes its performance is not good,. In our previous paper, two transformations, NWFE-Transformation and Liu-Transformation are considered. The results showed that the SVM with our Liu-Transformation algorithm has...
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