Clustering is one of the most important research areas in the field of data mining. In simple words, clustering is a division of data into different groups. Data are grouped into clusters in such a way that data of the same group are similar and those in other groups are dissimilar. It aims to minimize intra-class similarity while to maximize interclass dissimilarity. Clustering is an unsupervi...

In this paper, we firstly give a brief introduction of expectation maximization (EM) algorithm, and then discuss the initial value sensitivity of expectation maximization algorithm. Subsequently, we give a short proof of EM's convergence. Then, we implement experiments with the expectation maximization algorithm (We implement all the experiments on Gaussion mixture model (GMM) ). Our experiment...

We propose a new class of distances for the purpose of data clustering, called the geodesic distance, and introduce a geodesic extension of K-medoids algorithm. We analyze the theoretical properties of the geodesic distance within a clustering framework and prove that the geodesic K-medoids algorithm converges to the correct clustering assignment in the asymptotic regime, even in the presence o...

In this paper we introduce the Minkowski weighted partition around medoids algorithm (MW-PAM). This extends the popular partition around medoids algorithm (PAM) by automatically assigning K weights to each feature in a dataset, where K is the number of clusters. Our approach utilizes the within-cluster variance of features to calculate the weights and uses the Minkowski metric. We show through ...

In the k-medoid problem, given a dataset P, we are asked to choose k points in P as the medoids. The optimal medoid set minimizes the average Euclidean distance between the points in P and their closest medoid. Finding the optimal k medoids is NP hard, and existing algorithms aim at approximate answers, i.e., they compute medoids that achieve a small, yet not minimal, average distance. Similarl...

Finding groups of individuals with similar activity patterns (a sequence of activities within a given time period, usually 24 hours) has become an important issue in models of activity-based approaches to travel demand analysis. This knowledge is critical to many activity-based models, and it aids our understanding of activity/travel behavior. This paper aims to develop a methodology for the cl...

A comfortable way of digitizing a new music composition is by using a pen-based recognition system, in which the digital score is created with the sole effort of the composition itself. In this kind of systems, the input consist of a set of pen strokes. However, it is hitherto unclear the different types of strokes that must be considered for this task. This paper presents an experimental study...