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  "Title": "Time Series Analysis Toolkit Based on Symbolic Aggregate\nDiscretization, i.e. SAX",
  "Description": "Implements time series z-normalization, SAX, HOT-SAX, VSM,\nSAX-VSM, RePair, and RRA algorithms facilitating time series\nmotif (i.e., recurrent pattern), discord (i.e., anomaly), and\ncharacteristic pattern discovery along with interpretable time\nseries classification.",
  "Authors@R": "person(\"Pavel\", \"Senin\", , \"seninp@gmail.com\", c(\"aut\", \"cre\"))",
  "URL": "https://github.com/jMotif/jmotif-R",
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  "Author": "Pavel Senin [aut, cre]",
  "Maintainer": "Pavel Senin <seninp@gmail.com>",
  "Repository": "https://cran.r-universe.dev",
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    "bags_to_tfidf",
    "cosine_dist",
    "cosine_sim",
    "early_abandoned_dist",
    "euclidean_dist",
    "find_discords_brute_force",
    "find_discords_hotsax",
    "find_discords_rra",
    "idx_to_letter",
    "is_equal_mindist",
    "is_equal_str",
    "letter_to_idx",
    "letters_to_idx",
    "manyseries_to_wordbag",
    "min_dist",
    "paa",
    "sax_by_chunking",
    "sax_distance_matrix",
    "sax_via_window",
    "series_to_chars",
    "series_to_string",
    "series_to_wordbag",
    "str_to_repair_grammar",
    "subseries",
    "znorm"
  ],
  "_datasets": [
    {
      "name": "CBF",
      "title": "A standard UCR Cylinder-Bell-Funnel dataset from http://www.cs.ucr.edu/~eamonn/time_series_data",
      "object": "CBF",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "ecg0606",
      "title": "A PHYSIONET dataset",
      "object": "ECG0606",
      "class": [
        "numeric"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "Gun_Point",
      "title": "A standard UCR Gun Point dataset from http://www.cs.ucr.edu/~eamonn/time_series_data",
      "object": "Gun_Point",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "alphabet_to_cuts",
      "title": "Translates an alphabet size into the array of corresponding SAX cut-lines built using the Normal distribution.",
      "topics": [
        "alphabet_to_cuts"
      ]
    },
    {
      "page": "bags_to_tfidf",
      "title": "Computes a TF-IDF weight vectors for a set of word bags.",
      "topics": [
        "bags_to_tfidf"
      ]
    },
    {
      "page": "CBF",
      "title": "A standard UCR Cylinder-Bell-Funnel dataset from http://www.cs.ucr.edu/~eamonn/time_series_data",
      "topics": [
        "CBF"
      ]
    },
    {
      "page": "cosine_dist",
      "title": "Computes the cosine similarity between numeric vectors",
      "topics": [
        "cosine_dist"
      ]
    },
    {
      "page": "cosine_sim",
      "title": "Computes the cosine distance value between a bag of words and a set of TF-IDF weight vectors.",
      "topics": [
        "cosine_sim"
      ]
    },
    {
      "page": "early_abandoned_dist",
      "title": "Finds the Euclidean distance between points, if distance is above the threshold, abandons the computation and returns NAN.",
      "topics": [
        "early_abandoned_dist"
      ]
    },
    {
      "page": "ecg0606",
      "title": "A PHYSIONET dataset",
      "topics": [
        "ecg0606"
      ]
    },
    {
      "page": "euclidean_dist",
      "title": "Finds the Euclidean distance between points.",
      "topics": [
        "euclidean_dist"
      ]
    },
    {
      "page": "find_discords_brute_force",
      "title": "Finds a discord using brute force algorithm.",
      "topics": [
        "find_discords_brute_force"
      ]
    },
    {
      "page": "find_discords_hotsax",
      "title": "Finds a discord (i.e. time series anomaly) with HOT-SAX. Usually works the best with lower sizes of discretization parameters: PAA and Alphabet.",
      "topics": [
        "find_discords_hotsax"
      ]
    },
    {
      "page": "find_discords_rra",
      "title": "Finds a discord with RRA (Rare Rule Anomaly) algorithm. Usually works the best with higher than that for HOT-SAX sizes of discretization parameters (i.e., PAA and Alphabet sizes).",
      "topics": [
        "find_discords_rra"
      ]
    },
    {
      "page": "Gun_Point",
      "title": "A standard UCR Gun Point dataset from http://www.cs.ucr.edu/~eamonn/time_series_data",
      "topics": [
        "Gun_Point"
      ]
    },
    {
      "page": "idx_to_letter",
      "title": "Get the ASCII letter by an index.",
      "topics": [
        "idx_to_letter"
      ]
    },
    {
      "page": "is_equal_mindist",
      "title": "Compares two strings using mindist.",
      "topics": [
        "is_equal_mindist"
      ]
    },
    {
      "page": "is_equal_str",
      "title": "Compares two strings using natural letter ordering.",
      "topics": [
        "is_equal_str"
      ]
    },
    {
      "page": "letter_to_idx",
      "title": "Get the index for an ASCII letter.",
      "topics": [
        "letter_to_idx"
      ]
    },
    {
      "page": "letters_to_idx",
      "title": "Get an ASCII indexes sequence for a given character array.",
      "topics": [
        "letters_to_idx"
      ]
    },
    {
      "page": "manyseries_to_wordbag",
      "title": "Converts a set of time-series into a single bag of words.",
      "topics": [
        "manyseries_to_wordbag"
      ]
    },
    {
      "page": "min_dist",
      "title": "Computes the mindist value for two strings",
      "topics": [
        "min_dist"
      ]
    },
    {
      "page": "paa",
      "title": "Computes a Piecewise Aggregate Approximation (PAA) for a time series.",
      "topics": [
        "paa"
      ]
    },
    {
      "page": "sax_by_chunking",
      "title": "Discretize a time series with SAX using chunking (no sliding window).",
      "topics": [
        "sax_by_chunking"
      ]
    },
    {
      "page": "sax_distance_matrix",
      "title": "Generates a SAX MinDist distance matrix (i.e. the \"lookup table\") for a given alphabet size.",
      "topics": [
        "sax_distance_matrix"
      ]
    },
    {
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      "title": "Discretizes a time series with SAX via sliding window.",
      "topics": [
        "sax_via_window"
      ]
    },
    {
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      "title": "Transforms a time series into the char array using SAX and the normal alphabet.",
      "topics": [
        "series_to_chars"
      ]
    },
    {
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      "title": "Transforms a time series into the string.",
      "topics": [
        "series_to_string"
      ]
    },
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      "topics": [
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      ]
    },
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      "topics": [
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      ]
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      "topics": [
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      ]
    },
    {
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      "title": "Z-normalizes a time series by subtracting its mean and dividing by the standard deviation.",
      "topics": [
        "znorm"
      ]
    }
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