The dimension of the data is reduced from two dimensions to one dimension (not much choice in this case) and this is done by projecting on the direction of the $v2$ vector (after a rotation where $v2$ becomes parallel or perpendicular to one of the axes). Should I ask these as a new question? What were the poems other than those by Donne in the Melford Hall manuscript? After executing PCA or LSA, traditional algorithms like k-means or agglomerative methods are applied on the reduced term space and typical similarity measures, like cosine distance are used. Figure 4 was made with Plotly and shows some clearly defined clusters in the data. The hierarchical clustering dendrogram is often represented together with a heatmap that shows the entire data matrix, with entries color-coded according to their value. Since the dimensions don't correspond to actual words, it's rather a difficult issue. It only takes a minute to sign up. K-means was repeated $100$ times with random seeds to ensure convergence to the global optimum. and the documentation of flexmix and poLCA packages in R, including the following papers: Linzer, D. A., & Lewis, J. If the clustering algorithm metric does not depend on magnitude (say cosine distance) then the last normalization step can be omitted. amoeba, thank you for digesting the being discussed article to us all and for delivering your conclusions (+2); and for letting me personally know! It only takes a minute to sign up. Both of these approaches keep the number of data points constant, while reducing the "feature" dimensions. And should they be normalized again after that? Stack Exchange network consists of 181 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. What is Wario dropping at the end of Super Mario Land 2 and why? a certain category, in order to explore its attributes (for example, which Browse other questions tagged, Start here for a quick overview of the site, Detailed answers to any questions you might have, Discuss the workings and policies of this site. Making statements based on opinion; back them up with references or personal experience. I have no idea; the point is (please) to use one term for one thing and not two; otherwise your question is even more difficult to understand. Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization.
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