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| <table style="width: 100%;"><tr><td>spark.findFrequentSequentialPatterns {SparkR}</td><td style="text-align: right;">R Documentation</td></tr></table> |
| |
| <h2>PrefixSpan</h2> |
| |
| <h3>Description</h3> |
| |
| <p>A parallel PrefixSpan algorithm to mine frequent sequential patterns. |
| <code>spark.findFrequentSequentialPatterns</code> returns a complete set of frequent sequential |
| patterns. |
| For more details, see |
| <a href="https://spark.apache.org/docs/latest/mllib-frequent-pattern-mining.html#prefixspan"> |
| PrefixSpan</a>. |
| </p> |
| |
| |
| <h3>Usage</h3> |
| |
| <pre><code class='language-R'>spark.findFrequentSequentialPatterns(data, ...) |
| |
| ## S4 method for signature 'SparkDataFrame' |
| spark.findFrequentSequentialPatterns( |
| data, |
| minSupport = 0.1, |
| maxPatternLength = 10L, |
| maxLocalProjDBSize = 32000000L, |
| sequenceCol = "sequence" |
| ) |
| </code></pre> |
| |
| |
| <h3>Arguments</h3> |
| |
| <table> |
| <tr style="vertical-align: top;"><td><code>data</code></td> |
| <td> |
| <p>A SparkDataFrame.</p> |
| </td></tr> |
| <tr style="vertical-align: top;"><td><code>...</code></td> |
| <td> |
| <p>additional argument(s) passed to the method.</p> |
| </td></tr> |
| <tr style="vertical-align: top;"><td><code>minSupport</code></td> |
| <td> |
| <p>Minimal support level.</p> |
| </td></tr> |
| <tr style="vertical-align: top;"><td><code>maxPatternLength</code></td> |
| <td> |
| <p>Maximal pattern length.</p> |
| </td></tr> |
| <tr style="vertical-align: top;"><td><code>maxLocalProjDBSize</code></td> |
| <td> |
| <p>Maximum number of items (including delimiters used in the internal |
| storage format) allowed in a projected database before local |
| processing.</p> |
| </td></tr> |
| <tr style="vertical-align: top;"><td><code>sequenceCol</code></td> |
| <td> |
| <p>name of the sequence column in dataset.</p> |
| </td></tr> |
| </table> |
| |
| |
| <h3>Value</h3> |
| |
| <p>A complete set of frequent sequential patterns in the input sequences of itemsets. |
| The returned <code>SparkDataFrame</code> contains columns of sequence and corresponding |
| frequency. The schema of it will be: |
| <code>sequence: ArrayType(ArrayType(T))</code>, <code>freq: integer</code> |
| where T is the item type |
| </p> |
| |
| |
| <h3>Note</h3> |
| |
| <p>spark.findFrequentSequentialPatterns(SparkDataFrame) since 3.0.0 |
| </p> |
| |
| |
| <h3>Examples</h3> |
| |
| <pre><code class="language-r">## Not run: |
| ##D df <- createDataFrame(list(list(list(list(1L, 2L), list(3L))), |
| ##D list(list(list(1L), list(3L, 2L), list(1L, 2L))), |
| ##D list(list(list(1L, 2L), list(5L))), |
| ##D list(list(list(6L)))), |
| ##D schema = c("sequence")) |
| ##D frequency <- spark.findFrequentSequentialPatterns(df, minSupport = 0.5, maxPatternLength = 5L, |
| ##D maxLocalProjDBSize = 32000000L) |
| ##D showDF(frequency) |
| ## End(Not run) |
| </code></pre> |
| |
| |
| <hr /><div style="text-align: center;">[Package <em>SparkR</em> version 3.2.3 <a href="00Index.html">Index</a>]</div> |
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