Commit 43489a9b authored by dmattek's avatar dmattek

Modified help text

parent f173370e
...@@ -9,13 +9,13 @@ helpText.clHier = c(alertNAsPresentClDTW = paste0("NAs (still) present. DTW cann ...@@ -9,13 +9,13 @@ helpText.clHier = c(alertNAsPresentClDTW = paste0("NAs (still) present. DTW cann
alertNAsPresentCl = paste0("NAs (still) present, caution recommended. If interpolation is active in the left panel, ", alertNAsPresentCl = paste0("NAs (still) present, caution recommended. If interpolation is active in the left panel, ",
"missing data can be due to removed outlier time points."), "missing data can be due to removed outlier time points."),
alLearnMore = paste0("<p><a href=\"https://en.wikipedia.org/wiki/Hierarchical_clustering\" target=\"_blank\" title=\"External link\">Agglomerative hierarchical clustering</a> ", alLearnMore = paste0("<p><a href=\"https://en.wikipedia.org/wiki/Hierarchical_clustering\" target=\"_blank\" title=\"External link\">Agglomerative hierarchical clustering</a> ",
"initially assumes that all time series are forming their own clusters. It then grows a clustering dendrogram thanks to 2 inputs:<p>", "initially assumes that all time series are forming their own clusters. It then grows a clustering dendrogram using two inputs:<p>",
"First, a <b>dissimilarity matrix</b> between all pairs ", "A <b>dissimilarity matrix</b> between all pairs ",
"of time series is calculated with one of the metrics, such as ", "of time series is calculated with one of the metrics, such as ",
"Euclidean (<a href=\"https://en.wikipedia.org/wiki/Euclidean_distance\" target=\"_blank\" title=\"External link\">L2 norm</a>) ", "Euclidean (<a href=\"https://en.wikipedia.org/wiki/Euclidean_distance\" target=\"_blank\" title=\"External link\">L2 norm</a>), ",
"or Manhattan (<a href=\"https://en.wikipedia.org/wiki/Taxicab_geometry\" target=\"_blank\" title=\"External link\">L1 norm</a>) distance. ", "Manhattan (<a href=\"https://en.wikipedia.org/wiki/Taxicab_geometry\" target=\"_blank\" title=\"External link\">L1 norm</a>), or ",
"<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). ",
"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. ", "Instead of comparing time series point by point, DTW tries to align and match their shapes. ",
"This makes DTW a good quantification of similarity when signals are similar but shifted in time.</p>", "This makes DTW a good quantification of similarity when signals are similar but shifted in time.</p>",
"<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> ", "<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>"))
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