Data Mining

Many partitional clustering algorithms that automatically determine the number of clusters claim that this is an advantage. List two situations in which this is not the case. Please respond to two of your peer’s posts. Thank you. Need 400 - 450 Words. No plagiarism.Two References. Post 1: Partitional clustering algorithms are capable of calibrating and determining the number of clusters necessary in a given situation automatically.However, it is not the case when we are dealing with large sets of data, since clustering algorithms are only effective in automatically determining the number of clusters with smaller data sets. Therefore, when it comes to larger data sets it is not efficient in utilizing clustering algorithms.Another case where clustering algorithms are ineffective is that, once the merging/splitting decisions are made by the algorithm, users are unable to make any corrections. References: Omran, Mahamed & Engelbrecht, Andries & Salman, Ayed. (2007). An overview of clustering methods. Intell. Data Anal.. 11. 583-605. 10.3233/IDA-2007-11602. Tan, P. N., Steinbach, M., & Kumar, V. (2016). Introduction to data mining. Pearson Education India. Need Reply Post 200 - 250 Words No plagiarism. One reference. Post 2: Introduction: Partitional clustering algorithms: Partitional clustering can be defined as clustering methods that are used to observe and classify several data sets and the objects within the data set depending on the similarity. Every cluster is truly represented by the means of the data points that belong to the cluster. Disadvantages of clustering algorithms: Unable to make corrections when merging or separation takes place obscurity of termination criteria Non-effective in high dimensions Lack of interpretation of cluster description (Celebi, 2016) References: Celebi, M. E. (2016). Partitional clustering algorithms. Place of publication not identified: Springer International Pu. N’Cir, C. B., Cleuziou, G., & Essoussi, N. (2014). Overview of Overlapping Partitional Clustering Methods. Partitional Clustering Algorithms, 245-275. doi:10.1007/978-3-319-09259-1_8 Partitional Clustering Algorithms. (2015). doi:10.1007/978-3-319-09259-1 Need Reply Post 200 - 250 Words. No plagiarism. One reference.