"<a href=\"https://en.wikipedia.org/wiki/Dynamic_time_warping\" target=\"_blank\" title=\"External link\">Dynamic Time Warping</a> (DTW) ",
"<a href=\"https://en.wikipedia.org/wiki/Dynamic_time_warping\" target=\"_blank\" title=\"External link\">Dynamic Time Warping</a> (DTW) ",
"also quantifies similarity between two time series but ",
"is another distance metric that does not only compare series point by point but also tries to align them such that shapes between the 2 series are matched. ",
"contrary to other distance measures it accounts for the order of time points.</p>",
"This makes DTW a good quantification of similarity when signals are similar but shifted in time.</p>",
"<p>In the second step, distances are arranged hierarchicaly and visualised as a dendrogram ",
"<p>In the second step, clusters are successively built and merged together. The distance between the newly formed clusters is determined by the <b>linkage criterion</b> ",
"using one of <a href=\"https://en.wikipedia.org/wiki/Hierarchical_clustering\" target=\"_blank\" title=\"External link\">linkage methods</a>.</p>"))
"using one of <a href=\"https://en.wikipedia.org/wiki/Hierarchical_clustering\" target=\"_blank\" title=\"External link\">linkage methods</a>.</p>"))