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| <h1>SimilarityAnalysis</h1> |
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| <div id="comment" class="fullcommenttop"><div class="comment cmt"><p>Based on "Ted Dunnning & Ellen Friedman: Practical Machine Learning, Innovations in Recommendation", |
| available at http://www.mapr.com/practical-machine-learning</p><p>see also "Sebastian Schelter, Christoph Boden, Volker Markl: |
| Scalable Similarity-Based Neighborhood Methods with MapReduce |
| ACM Conference on Recommender Systems 2012" |
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| </li><li name="org.apache.mahout.math.cf.SimilarityAnalysis#computeSimilarities" visbl="pub" data-isabs="false" fullComment="no" group="Ungrouped"> |
| <a id="computeSimilarities(drm:org.apache.mahout.math.drm.DrmLike[Int],numUsers:Int,maxInterestingItemsPerThing:Int,bcastNumInteractionsB:org.apache.mahout.math.drm.BCast[org.apache.mahout.math.Vector],bcastNumInteractionsA:org.apache.mahout.math.drm.BCast[org.apache.mahout.math.Vector],crossCooccurrence:Boolean,minLLROpt:Option[Double]):org.apache.mahout.math.drm.DrmLike[Int]"></a> |
| <a id="computeSimilarities(DrmLike[Int],Int,Int,BCast[Vector],BCast[Vector],Boolean,Option[Double]):DrmLike[Int]"></a> |
| <h4 class="signature"> |
| <span class="modifier_kind"> |
| <span class="modifier"></span> |
| <span class="kind">def</span> |
| </span> |
| <span class="symbol"> |
| <span class="name">computeSimilarities</span><span class="params">(<span name="drm">drm: <a href="../drm/DrmLike.html" class="extype" name="org.apache.mahout.math.drm.DrmLike">DrmLike</a>[<span class="extype" name="scala.Int">Int</span>]</span>, <span name="numUsers">numUsers: <span class="extype" name="scala.Int">Int</span></span>, <span name="maxInterestingItemsPerThing">maxInterestingItemsPerThing: <span class="extype" name="scala.Int">Int</span></span>, <span name="bcastNumInteractionsB">bcastNumInteractionsB: <a href="../drm/BCast.html" class="extype" name="org.apache.mahout.math.drm.BCast">BCast</a>[<span class="extype" name="org.apache.mahout.math.Vector">Vector</span>]</span>, <span name="bcastNumInteractionsA">bcastNumInteractionsA: <a href="../drm/BCast.html" class="extype" name="org.apache.mahout.math.drm.BCast">BCast</a>[<span class="extype" name="org.apache.mahout.math.Vector">Vector</span>]</span>, <span name="crossCooccurrence">crossCooccurrence: <span class="extype" name="scala.Boolean">Boolean</span> = <span class="symbol">true</span></span>, <span name="minLLROpt">minLLROpt: <span class="extype" name="scala.Option">Option</span>[<span class="extype" name="scala.Double">Double</span>] = <span class="symbol">None</span></span>)</span><span class="result">: <a href="../drm/DrmLike.html" class="extype" name="org.apache.mahout.math.drm.DrmLike">DrmLike</a>[<span class="extype" name="scala.Int">Int</span>]</span> |
| </span> |
| </h4> |
| |
| </li><li name="org.apache.mahout.math.cf.SimilarityAnalysis#cooccurrences" visbl="pub" data-isabs="false" fullComment="yes" group="Ungrouped"> |
| <a id="cooccurrences(drmARaw:org.apache.mahout.math.drm.DrmLike[Int],randomSeed:Int,maxInterestingItemsPerThing:Int,maxNumInteractions:Int,drmBs:Array[org.apache.mahout.math.drm.DrmLike[Int]],parOpts:org.apache.mahout.math.cf.ParOpts):List[org.apache.mahout.math.drm.DrmLike[Int]]"></a> |
| <a id="cooccurrences(DrmLike[Int],Int,Int,Int,Array[DrmLike[Int]],ParOpts):List[DrmLike[Int]]"></a> |
| <h4 class="signature"> |
| <span class="modifier_kind"> |
| <span class="modifier"></span> |
| <span class="kind">def</span> |
| </span> |
| <span class="symbol"> |
| <span class="name">cooccurrences</span><span class="params">(<span name="drmARaw">drmARaw: <a href="../drm/DrmLike.html" class="extype" name="org.apache.mahout.math.drm.DrmLike">DrmLike</a>[<span class="extype" name="scala.Int">Int</span>]</span>, <span name="randomSeed">randomSeed: <span class="extype" name="scala.Int">Int</span> = <span class="symbol">0xdeadbeef</span></span>, <span name="maxInterestingItemsPerThing">maxInterestingItemsPerThing: <span class="extype" name="scala.Int">Int</span> = <span class="symbol">50</span></span>, <span name="maxNumInteractions">maxNumInteractions: <span class="extype" name="scala.Int">Int</span> = <span class="symbol">500</span></span>, <span name="drmBs">drmBs: <span class="extype" name="scala.Array">Array</span>[<a href="../drm/DrmLike.html" class="extype" name="org.apache.mahout.math.drm.DrmLike">DrmLike</a>[<span class="extype" name="scala.Int">Int</span>]] = <span class="symbol">Array()</span></span>, <span name="parOpts">parOpts: <a href="ParOpts.html" class="extype" name="org.apache.mahout.math.cf.ParOpts">ParOpts</a> = <span class="symbol"><span class="name"><a href="#defaultParOpts:org.apache.mahout.math.cf.ParOpts">defaultParOpts</a></span></span></span>)</span><span class="result">: <span class="extype" name="scala.List">List</span>[<a href="../drm/DrmLike.html" class="extype" name="org.apache.mahout.math.drm.DrmLike">DrmLike</a>[<span class="extype" name="scala.Int">Int</span>]]</span> |
| </span> |
| </h4> |
| <p class="shortcomment cmt">Calculates item (column-wise) similarity using the log-likelihood ratio on A'A, A'B, A'C, .</p><div class="fullcomment"><div class="comment cmt"><p>Calculates item (column-wise) similarity using the log-likelihood ratio on A'A, A'B, A'C, ... |
| and returns a list of similarity and cross-similarity matrices |
| </p></div><dl class="paramcmts block"><dt class="param">drmARaw</dt><dd class="cmt"><p>Primary interaction matrix</p></dd><dt class="param">randomSeed</dt><dd class="cmt"><p>when kept to a constant will make repeatable downsampling</p></dd><dt class="param">maxInterestingItemsPerThing</dt><dd class="cmt"><p>number of similar items to return per item, default: 50</p></dd><dt class="param">maxNumInteractions</dt><dd class="cmt"><p>max number of interactions after downsampling, default: 500</p></dd><dt class="param">parOpts</dt><dd class="cmt"><p>partitioning params for drm.par(...)</p></dd><dt>returns</dt><dd class="cmt"><p>a list of <a href="../drm/DrmLike.html" class="extype" name="org.apache.mahout.math.drm.DrmLike">org.apache.mahout.math.drm.DrmLike</a> containing downsampled DRMs for cooccurrence and |
| cross-cooccurrence |
| </p></dd></dl></div> |
| </li><li name="org.apache.mahout.math.cf.SimilarityAnalysis#cooccurrencesIDSs" visbl="pub" data-isabs="false" fullComment="yes" group="Ungrouped"> |
| <a id="cooccurrencesIDSs(indexedDatasets:Array[org.apache.mahout.math.indexeddataset.IndexedDataset],randomSeed:Int,maxInterestingItemsPerThing:Int,maxNumInteractions:Int,parOpts:org.apache.mahout.math.cf.ParOpts):List[org.apache.mahout.math.indexeddataset.IndexedDataset]"></a> |
| <a id="cooccurrencesIDSs(Array[IndexedDataset],Int,Int,Int,ParOpts):List[IndexedDataset]"></a> |
| <h4 class="signature"> |
| <span class="modifier_kind"> |
| <span class="modifier"></span> |
| <span class="kind">def</span> |
| </span> |
| <span class="symbol"> |
| <span class="name">cooccurrencesIDSs</span><span class="params">(<span name="indexedDatasets">indexedDatasets: <span class="extype" name="scala.Array">Array</span>[<a href="../indexeddataset/IndexedDataset.html" class="extype" name="org.apache.mahout.math.indexeddataset.IndexedDataset">IndexedDataset</a>]</span>, <span name="randomSeed">randomSeed: <span class="extype" name="scala.Int">Int</span> = <span class="symbol">0xdeadbeef</span></span>, <span name="maxInterestingItemsPerThing">maxInterestingItemsPerThing: <span class="extype" name="scala.Int">Int</span> = <span class="symbol">50</span></span>, <span name="maxNumInteractions">maxNumInteractions: <span class="extype" name="scala.Int">Int</span> = <span class="symbol">500</span></span>, <span name="parOpts">parOpts: <a href="ParOpts.html" class="extype" name="org.apache.mahout.math.cf.ParOpts">ParOpts</a> = <span class="symbol"><span class="name"><a href="#defaultParOpts:org.apache.mahout.math.cf.ParOpts">defaultParOpts</a></span></span></span>)</span><span class="result">: <span class="extype" name="scala.List">List</span>[<a href="../indexeddataset/IndexedDataset.html" class="extype" name="org.apache.mahout.math.indexeddataset.IndexedDataset">IndexedDataset</a>]</span> |
| </span> |
| </h4> |
| <p class="shortcomment cmt">Calculates item (column-wise) similarity using the log-likelihood ratio on A'A, A'B, A'C, .</p><div class="fullcomment"><div class="comment cmt"><p>Calculates item (column-wise) similarity using the log-likelihood ratio on A'A, A'B, A'C, ... and returns |
| a list of similarity and cross-similarity matrices. Somewhat easier to use method, which handles the ID |
| dictionaries correctly |
| </p></div><dl class="paramcmts block"><dt class="param">indexedDatasets</dt><dd class="cmt"><p>first in array is primary/A matrix all others are treated as secondary</p></dd><dt class="param">randomSeed</dt><dd class="cmt"><p>use default to make repeatable, otherwise pass in system time or some randomizing seed</p></dd><dt class="param">maxInterestingItemsPerThing</dt><dd class="cmt"><p>max similarities per items</p></dd><dt class="param">maxNumInteractions</dt><dd class="cmt"><p>max number of input items per item</p></dd><dt class="param">parOpts</dt><dd class="cmt"><p>partitioning params for drm.par(...)</p></dd><dt>returns</dt><dd class="cmt"><p>a list of <a href="../indexeddataset/IndexedDataset.html" class="extype" name="org.apache.mahout.math.indexeddataset.IndexedDataset">org.apache.mahout.math.indexeddataset.IndexedDataset</a> containing downsampled |
| IndexedDatasets for cooccurrence and cross-cooccurrence |
| </p></dd></dl></div> |
| </li><li name="org.apache.mahout.math.cf.SimilarityAnalysis#crossOccurrenceDownsampled" visbl="pub" data-isabs="false" fullComment="yes" group="Ungrouped"> |
| <a id="crossOccurrenceDownsampled(datasets:List[org.apache.mahout.math.cf.DownsamplableCrossOccurrenceDataset],randomSeed:Int):List[org.apache.mahout.math.indexeddataset.IndexedDataset]"></a> |
| <a id="crossOccurrenceDownsampled(List[DownsamplableCrossOccurrenceDataset],Int):List[IndexedDataset]"></a> |
| <h4 class="signature"> |
| <span class="modifier_kind"> |
| <span class="modifier"></span> |
| <span class="kind">def</span> |
| </span> |
| <span class="symbol"> |
| <span class="name">crossOccurrenceDownsampled</span><span class="params">(<span name="datasets">datasets: <span class="extype" name="scala.List">List</span>[<a href="DownsamplableCrossOccurrenceDataset.html" class="extype" name="org.apache.mahout.math.cf.DownsamplableCrossOccurrenceDataset">DownsamplableCrossOccurrenceDataset</a>]</span>, <span name="randomSeed">randomSeed: <span class="extype" name="scala.Int">Int</span> = <span class="symbol">0xdeadbeef</span></span>)</span><span class="result">: <span class="extype" name="scala.List">List</span>[<a href="../indexeddataset/IndexedDataset.html" class="extype" name="org.apache.mahout.math.indexeddataset.IndexedDataset">IndexedDataset</a>]</span> |
| </span> |
| </h4> |
| <p class="shortcomment cmt">Calculates item (column-wise) similarity using the log-likelihood ratio on A'A, A'B, A'C, .</p><div class="fullcomment"><div class="comment cmt"><p>Calculates item (column-wise) similarity using the log-likelihood ratio on A'A, A'B, A'C, ... and returns |
| a list of similarity and cross-occurrence matrices. Somewhat easier to use method, which handles the ID |
| dictionaries correctly and contains info about downsampling in each model calc. |
| </p></div><dl class="paramcmts block"><dt class="param">datasets</dt><dd class="cmt"><p>first in array is primary/A matrix all others are treated as secondary, includes information |
| used to downsample the input drm as well as the output llr(A'A), llr(A'B). The information |
| is contained in each dataset in the array and applies to the model calculation of A' with |
| the dataset. Todo: ignoring absolute threshold for now.</p></dd><dt class="param">randomSeed</dt><dd class="cmt"><p>use default to make repeatable, otherwise pass in system time or some randomizing seed</p></dd><dt>returns</dt><dd class="cmt"><p>a list of <a href="../indexeddataset/IndexedDataset.html" class="extype" name="org.apache.mahout.math.indexeddataset.IndexedDataset">org.apache.mahout.math.indexeddataset.IndexedDataset</a> containing downsampled |
| IndexedDatasets for cooccurrence and cross-cooccurrence |
| </p></dd></dl></div> |
| </li><li name="org.apache.mahout.math.cf.SimilarityAnalysis#defaultParOpts" visbl="pub" data-isabs="false" fullComment="no" group="Ungrouped"> |
| <a id="defaultParOpts:org.apache.mahout.math.cf.ParOpts"></a> |
| <a id="defaultParOpts:ParOpts"></a> |
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| <span class="modifier_kind"> |
| <span class="modifier"></span> |
| <span class="kind">lazy val</span> |
| </span> |
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| <span class="name">defaultParOpts</span><span class="result">: <a href="ParOpts.html" class="extype" name="org.apache.mahout.math.cf.ParOpts">ParOpts</a></span> |
| </span> |
| </h4> |
| |
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| <a id="logLikelihoodRatio(numInteractionsWithA:Long,numInteractionsWithB:Long,numInteractionsWithAandB:Long,numInteractions:Long):Double"></a> |
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| <span class="name">logLikelihoodRatio</span><span class="params">(<span name="numInteractionsWithA">numInteractionsWithA: <span class="extype" name="scala.Long">Long</span></span>, <span name="numInteractionsWithB">numInteractionsWithB: <span class="extype" name="scala.Long">Long</span></span>, <span name="numInteractionsWithAandB">numInteractionsWithAandB: <span class="extype" name="scala.Long">Long</span></span>, <span name="numInteractions">numInteractions: <span class="extype" name="scala.Long">Long</span></span>)</span><span class="result">: <span class="extype" name="scala.Double">Double</span></span> |
| </span> |
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| <p class="shortcomment cmt">Compute loglikelihood ratio see http://tdunning.</p><div class="fullcomment"><div class="comment cmt"><p>Compute loglikelihood ratio see http://tdunning.blogspot.de/2008/03/surprise-and-coincidence.html for details</p></div></div> |
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| </li><li name="org.apache.mahout.math.cf.SimilarityAnalysis#rowSimilarity" visbl="pub" data-isabs="false" fullComment="yes" group="Ungrouped"> |
| <a id="rowSimilarity(drmARaw:org.apache.mahout.math.drm.DrmLike[Int],randomSeed:Int,maxInterestingSimilaritiesPerRow:Int,maxNumInteractions:Int,parOpts:org.apache.mahout.math.cf.ParOpts):org.apache.mahout.math.drm.DrmLike[Int]"></a> |
| <a id="rowSimilarity(DrmLike[Int],Int,Int,Int,ParOpts):DrmLike[Int]"></a> |
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| <span class="modifier_kind"> |
| <span class="modifier"></span> |
| <span class="kind">def</span> |
| </span> |
| <span class="symbol"> |
| <span class="name">rowSimilarity</span><span class="params">(<span name="drmARaw">drmARaw: <a href="../drm/DrmLike.html" class="extype" name="org.apache.mahout.math.drm.DrmLike">DrmLike</a>[<span class="extype" name="scala.Int">Int</span>]</span>, <span name="randomSeed">randomSeed: <span class="extype" name="scala.Int">Int</span> = <span class="symbol">0xdeadbeef</span></span>, <span name="maxInterestingSimilaritiesPerRow">maxInterestingSimilaritiesPerRow: <span class="extype" name="scala.Int">Int</span> = <span class="symbol">50</span></span>, <span name="maxNumInteractions">maxNumInteractions: <span class="extype" name="scala.Int">Int</span> = <span class="symbol">500</span></span>, <span name="parOpts">parOpts: <a href="ParOpts.html" class="extype" name="org.apache.mahout.math.cf.ParOpts">ParOpts</a> = <span class="symbol"><span class="name"><a href="#defaultParOpts:org.apache.mahout.math.cf.ParOpts">defaultParOpts</a></span></span></span>)</span><span class="result">: <a href="../drm/DrmLike.html" class="extype" name="org.apache.mahout.math.drm.DrmLike">DrmLike</a>[<span class="extype" name="scala.Int">Int</span>]</span> |
| </span> |
| </h4> |
| <p class="shortcomment cmt">Calculates row-wise similarity using the log-likelihood ratio on AA' and returns a DRM of rows and similar rows |
| </p><div class="fullcomment"><div class="comment cmt"><p>Calculates row-wise similarity using the log-likelihood ratio on AA' and returns a DRM of rows and similar rows |
| </p></div><dl class="paramcmts block"><dt class="param">drmARaw</dt><dd class="cmt"><p>Primary interaction matrix</p></dd><dt class="param">randomSeed</dt><dd class="cmt"><p>when kept to a constant will make repeatable downsampling</p></dd><dt class="param">maxInterestingSimilaritiesPerRow</dt><dd class="cmt"><p>number of similar items to return per item, default: 50</p></dd><dt class="param">maxNumInteractions</dt><dd class="cmt"><p>max number of interactions after downsampling, default: 500</p></dd><dt class="param">parOpts</dt><dd class="cmt"><p>partitioning options used for drm.par(...) |
| </p></dd></dl></div> |
| </li><li name="org.apache.mahout.math.cf.SimilarityAnalysis#rowSimilarityIDS" visbl="pub" data-isabs="false" fullComment="yes" group="Ungrouped"> |
| <a id="rowSimilarityIDS(indexedDataset:org.apache.mahout.math.indexeddataset.IndexedDataset,randomSeed:Int,maxInterestingSimilaritiesPerRow:Int,maxObservationsPerRow:Int):org.apache.mahout.math.indexeddataset.IndexedDataset"></a> |
| <a id="rowSimilarityIDS(IndexedDataset,Int,Int,Int):IndexedDataset"></a> |
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| <span class="modifier_kind"> |
| <span class="modifier"></span> |
| <span class="kind">def</span> |
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| <span class="name">rowSimilarityIDS</span><span class="params">(<span name="indexedDataset">indexedDataset: <a href="../indexeddataset/IndexedDataset.html" class="extype" name="org.apache.mahout.math.indexeddataset.IndexedDataset">IndexedDataset</a></span>, <span name="randomSeed">randomSeed: <span class="extype" name="scala.Int">Int</span> = <span class="symbol">0xdeadbeef</span></span>, <span name="maxInterestingSimilaritiesPerRow">maxInterestingSimilaritiesPerRow: <span class="extype" name="scala.Int">Int</span> = <span class="symbol">50</span></span>, <span name="maxObservationsPerRow">maxObservationsPerRow: <span class="extype" name="scala.Int">Int</span> = <span class="symbol">500</span></span>)</span><span class="result">: <a href="../indexeddataset/IndexedDataset.html" class="extype" name="org.apache.mahout.math.indexeddataset.IndexedDataset">IndexedDataset</a></span> |
| </span> |
| </h4> |
| <p class="shortcomment cmt">Calculates row-wise similarity using the log-likelihood ratio on AA' and returns a drm of rows and similar rows.</p><div class="fullcomment"><div class="comment cmt"><p>Calculates row-wise similarity using the log-likelihood ratio on AA' and returns a drm of rows and similar rows. |
| Uses IndexedDatasets, which handle external ID dictionaries properly |
| </p></div><dl class="paramcmts block"><dt class="param">indexedDataset</dt><dd class="cmt"><p>compare each row to every other</p></dd><dt class="param">randomSeed</dt><dd class="cmt"><p>use default to make repeatable, otherwise pass in system time or some randomizing seed</p></dd><dt class="param">maxInterestingSimilaritiesPerRow</dt><dd class="cmt"><p>max elements returned in each row</p></dd><dt class="param">maxObservationsPerRow</dt><dd class="cmt"><p>max number of input elements to use |
| </p></dd></dl></div> |
| </li><li name="org.apache.mahout.math.cf.SimilarityAnalysis#sampleDownAndBinarize" visbl="pub" data-isabs="false" fullComment="yes" group="Ungrouped"> |
| <a id="sampleDownAndBinarize(drmM:org.apache.mahout.math.drm.DrmLike[Int],seed:Int,maxNumInteractions:Int):org.apache.mahout.math.drm.DrmLike[Int]"></a> |
| <a id="sampleDownAndBinarize(DrmLike[Int],Int,Int):DrmLike[Int]"></a> |
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| <span class="name">sampleDownAndBinarize</span><span class="params">(<span name="drmM">drmM: <a href="../drm/DrmLike.html" class="extype" name="org.apache.mahout.math.drm.DrmLike">DrmLike</a>[<span class="extype" name="scala.Int">Int</span>]</span>, <span name="seed">seed: <span class="extype" name="scala.Int">Int</span></span>, <span name="maxNumInteractions">maxNumInteractions: <span class="extype" name="scala.Int">Int</span></span>)</span><span class="result">: <a href="../drm/DrmLike.html" class="extype" name="org.apache.mahout.math.drm.DrmLike">DrmLike</a>[<span class="extype" name="scala.Int">Int</span>]</span> |
| </span> |
| </h4> |
| <p class="shortcomment cmt">Selectively downsample rows and items with an anomalous amount of interactions, inspired by |
| https://github.</p><div class="fullcomment"><div class="comment cmt"><p>Selectively downsample rows and items with an anomalous amount of interactions, inspired by |
| https://github.com/tdunning/in-memory-cooccurrence/blob/master/src/main/java/com/tdunning/cooc/Analyze.java</p><p>additionally binarizes input matrix, as we're only interesting in knowing whether interactions happened or not |
| </p></div><dl class="paramcmts block"><dt class="param">drmM</dt><dd class="cmt"><p>matrix to downsample</p></dd><dt class="param">seed</dt><dd class="cmt"><p>random number generator seed, keep to a constant if repeatability is neccessary</p></dd><dt class="param">maxNumInteractions</dt><dd class="cmt"><p>number of elements in a row of the returned matrix</p></dd><dt>returns</dt><dd class="cmt"><p>the downsampled DRM |
| </p></dd></dl></div> |
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