Clusterability, Model Selection and Evaluation. Clustering is a central topic in unsupervised learning and has a wide variety of applications. However, the increasing needs of clustering massive datasets and the high cost of running clustering algorithms poses difficult problems for users, while to select the best clustering model with a suitable number of clusters is also a primary focus. In this thesis, we mainly focus on determining whether a data set is clusterable, and what is the natural number of clusters in a dataset. First, we approach data clusterability from an ultrametric-based perspective.
How to structure a dissertation
"Model Selection Procedures for Incomplete Data" by Ashok K. Chaurasia
Model Selection Procedures for Incomplete Data. Ashok K. Chaurasia , University of Connecticut - Storrs Follow. Model selection is a critical part of analysis of data in applied research. Equally ubiquitous is the notion of incomplete data sets and the challenges presented in analyzing data with missing values.
Model Selection and Stopping Rules for High-Dimensional Forward Selection
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A dissertation or thesis is a long piece of academic writing based on original research. This article helps you work out exactly what you should include and where to include it. You can also download our full dissertation template in. The template includes a ready-made table of contents with notes on what to include in each chapter. You can adapt it to your own requirements.