<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Algorithms on SAX-VSM</title><link>https://jmotif.github.io/sax-vsm_site/algorithm/</link><description>Recent content in Algorithms on SAX-VSM</description><generator>Hugo</generator><language>en</language><atom:link href="https://jmotif.github.io/sax-vsm_site/algorithm/index.xml" rel="self" type="application/rss+xml"/><item><title>Z-normalization of time series</title><link>https://jmotif.github.io/sax-vsm_site/algorithm/znorm/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://jmotif.github.io/sax-vsm_site/algorithm/znorm/</guid><description>Why and how time series are standardized to zero mean and unit variance before discretization.</description></item><item><title>Piecewise Aggregate Approximation (PAA)</title><link>https://jmotif.github.io/sax-vsm_site/algorithm/paa/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://jmotif.github.io/sax-vsm_site/algorithm/paa/</guid><description>Dimensionality reduction by frame averaging, and the lower-bounding PAA distance.</description></item><item><title>Symbolic Aggregate Approximation (SAX)</title><link>https://jmotif.github.io/sax-vsm_site/algorithm/sax/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://jmotif.github.io/sax-vsm_site/algorithm/sax/</guid><description>How SAX turns a real-valued time series into a string: PAA frames, Gaussian breakpoints, and the lower-bounding MINDIST — with a fully worked example.</description></item><item><title>Time series discretization via sliding window</title><link>https://jmotif.github.io/sax-vsm_site/algorithm/slidingwindowsax/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://jmotif.github.io/sax-vsm_site/algorithm/slidingwindowsax/</guid><description>How a sliding window turns one long time series into an ordered sequence of SAX words describing its local features.</description></item><item><title>SAX numerosity reduction</title><link>https://jmotif.github.io/sax-vsm_site/algorithm/numerosityreduction/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://jmotif.github.io/sax-vsm_site/algorithm/numerosityreduction/</guid><description>Collapsing runs of identical consecutive SAX words — smaller output, faster algorithms, and naturally variable-length patterns.</description></item><item><title>TF-IDF weighting for time series (tf·idf)</title><link>https://jmotif.github.io/sax-vsm_site/algorithm/tfidf/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://jmotif.github.io/sax-vsm_site/algorithm/tfidf/</guid><description>How term frequency and inverse document frequency turn per-class bags of SAX words into class-characteristic weight vectors.</description></item><item><title>Cosine similarity for time series classification</title><link>https://jmotif.github.io/sax-vsm_site/algorithm/cosine/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://jmotif.github.io/sax-vsm_site/algorithm/cosine/</guid><description>The angle-based similarity measure that scores an unlabeled time series against each class&amp;rsquo;s tf·idf weight vector.</description></item><item><title>Interpretable time series classification with SAX-VSM</title><link>https://jmotif.github.io/sax-vsm_site/algorithm/sax-vsm/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://jmotif.github.io/sax-vsm_site/algorithm/sax-vsm/</guid><description>The full SAX-VSM algorithm: per-class bags of SAX words, tf·idf weighting, and cosine-similarity classification.</description></item><item><title>SAX bitmap patterns visualization</title><link>https://jmotif.github.io/sax-vsm_site/algorithm/saxbitmap/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://jmotif.github.io/sax-vsm_site/algorithm/saxbitmap/</guid><description>Turning SAX word frequencies into color bitmaps for at-a-glance comparison of large time series collections.</description></item></channel></rss>