VQ-Based Clustering Algorithm of Piecewise- Dependent-Data
نویسندگان
چکیده
In this paper a piecewise-dependent-data (PDD) clustering algorithm is presented, and a proof of its convergence to a local minimum is given. A distortion measure-based model represents each cluster. The proposed algorithm is iterative. At the end of each iteration, a competition between the models is performed. Then the data is regrouped between the models. The “movement” of the data between the models and the retraining allows the minimization of the overall system distortion. The Kohonen Self-Organizing Map (SOM) was used as the VQ model for clustering. The clustering algorithm was tested using data generated from four generators of Continuous Density HMM (CDHMM). It was demonstrated that the overall distortion is a decreasing function.
منابع مشابه
An integrated heuristic method based on piecewise regression and cluster analysis for fluctuation data (A case study on health-care: Psoriasis patients)
Trend forecasting and proper understanding of the future changes is necessary for planning in health-care area.One of the problems of analytic methods is determination of the number and location of the breakpoints, especially for fluctuation data. In this area, few researches are published when number and location of the nodes are not specified.In this paper, a clustering-based method is develo...
متن کاملNGTSOM: A Novel Data Clustering Algorithm Based on Game Theoretic and Self- Organizing Map
Identifying clusters is an important aspect of data analysis. This paper proposes a noveldata clustering algorithm to increase the clustering accuracy. A novel game theoretic self-organizingmap (NGTSOM ) and neural gas (NG) are used in combination with Competitive Hebbian Learning(CHL) to improve the quality of the map and provide a better vector quantization (VQ) for clusteringdata. Different ...
متن کاملPrediction-Based Portfolio Optimization Model for Iran’s Oil Dependent Stocks Using Data Mining Methods
This study applied a prediction-based portfolio optimization model to explore the results of portfolio predicament in the Tehran Stock Exchange. To this aim, first, the data mining approach was used to predict the petroleum products and chemical industry using clustering stock market data. Then, some effective factors, such as crude oil price, exchange rate, global interest rate, gold price, an...
متن کاملMixed-lingual spoken word recognition by using VQ codebook sequences of variable length segments
We are investigating unsupervised phone modeling. This paper describes a derivation method of VQ codebook sequences of variable length segments from spoken word samples, and also describes evaluation results by applying the method to mixed-lingual speech recognition tasks which include non-native speakers. The VQ codebook is generated based on a piecewise linear segmentation method which includ...
متن کاملModified Convex Data Clustering Algorithm Based on Alternating Direction Method of Multipliers
Knowing the fact that the main weakness of the most standard methods including k-means and hierarchical data clustering is their sensitivity to initialization and trapping to local minima, this paper proposes a modification of convex data clustering in which there is no need to be peculiar about how to select initial values. Due to properly converting the task of optimization to an equivalent...
متن کامل