This study presents the results of an experimental study of two document clustering techniques which are kmeans and k-means++. In particular, we compare the two main approaches in crime document clustering. The drawback of k-means is that the user needs to define the centroid point. This becomes more critical when dealing with document clustering because each center point represented by a word ...

One of the most popular algorithms for clustering in Euclidean space is the k-means algorithm; k-means is difficult to analyze mathematically, and few theoretical guarantees are known about it, particularly when the data is well-clustered. In this paper, we attempt to fill this gap in the literature by analyzing the behavior of k-means on well-clustered data. In particular, we study the case wh...

 We consider the problem of estimation the population mean of the study variate Y in presence of measurement errors when information on an auxiliary character X is known. A class of estimators for population means using information on an auxiliary variate X is defined. Expressions for its asymptotic bias and mean square error are obtained. Optimum conditions are obtained for which the mean...

in defining the term social management strategy information, we can say, in short, that it is to organize social action aimed at solving problems of strategic policymaking and strategic planning of social services. direct service to the public not only means social welfare but also calls for constructive strategic policies in international atmosphere. smsi is the organized efforts of the societ...