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 <h1 title="Uses of Package org.apache.ignite.ml.dataset" class="title">Uses of Package<br>org.apache.ignite.ml.dataset</h1>
 </div>
 <div class="contentContainer">
 <ul class="blockList">
 <li class="blockList">
 <table class="useSummary" border="0" cellpadding="3" cellspacing="0" summary="Use table, listing packages, and an explanation">
 <caption><span>Packages that use <a href="../../../../../org/apache/ignite/ml/dataset/package-summary.html">org.apache.ignite.ml.dataset</a></span><span class="tabEnd">&nbsp;</span></caption>
 <tr>
 <th class="colFirst" scope="col">Package</th>
 <th class="colLast" scope="col">Description</th>
 </tr>
 <tbody>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.clustering.gmm">org.apache.ignite.ml.clustering.gmm</a></td>
 <td class="colLast">
 <div class="block">Contains Gauss Mixture Model clustering algorithm (see <a href="../../../../../org/apache/ignite/ml/clustering/gmm/GmmModel.html" title="class in org.apache.ignite.ml.clustering.gmm"><code>GmmModel</code></a>).</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.clustering.kmeans">org.apache.ignite.ml.clustering.kmeans</a></td>
 <td class="colLast">
 <div class="block">Contains kMeans clustering algorithm.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.composition.bagging">org.apache.ignite.ml.composition.bagging</a></td>
 <td class="colLast">&nbsp;</td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.composition.boosting">org.apache.ignite.ml.composition.boosting</a></td>
 <td class="colLast">
 <div class="block">Contains Gradient Boosting regression and classification abstract classes
  allowing regressor type selecting in child classes.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.composition.boosting.convergence">org.apache.ignite.ml.composition.boosting.convergence</a></td>
 <td class="colLast">
 <div class="block">Package contains implementation of convergence checking algorithms for gradient boosting.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.composition.boosting.convergence.mean">org.apache.ignite.ml.composition.boosting.convergence.mean</a></td>
 <td class="colLast">
 <div class="block">Contains implementation of convergence checking computer by mean of absolute value of errors in dataset.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.composition.boosting.convergence.median">org.apache.ignite.ml.composition.boosting.convergence.median</a></td>
 <td class="colLast">
 <div class="block">Contains implementation of convergence checking computer by median of medians of errors in dataset.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.composition.boosting.convergence.simple">org.apache.ignite.ml.composition.boosting.convergence.simple</a></td>
 <td class="colLast">
 <div class="block">Contains implementation of Stub for convergence checking.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.composition.combinators.parallel">org.apache.ignite.ml.composition.combinators.parallel</a></td>
 <td class="colLast">
 <div class="block">Contains parallel combiners (ensembles) of trainers and models.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.composition.combinators.sequential">org.apache.ignite.ml.composition.combinators.sequential</a></td>
 <td class="colLast">
 <div class="block">Contains sequential combinators of trainers and models.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.composition.stacking">org.apache.ignite.ml.composition.stacking</a></td>
 <td class="colLast">
 <div class="block">Contains classes used for training with stacking technique.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.dataset">org.apache.ignite.ml.dataset</a></td>
 <td class="colLast">
 <div class="block">Base package for machine learning dataset classes.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.dataset.impl.bootstrapping">org.apache.ignite.ml.dataset.impl.bootstrapping</a></td>
 <td class="colLast">
 <div class="block">Base package for bootstrapped implementation of machine learning dataset.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.dataset.impl.cache">org.apache.ignite.ml.dataset.impl.cache</a></td>
 <td class="colLast">
 <div class="block">Base package for cache based implementation of machine learning dataset.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.dataset.impl.cache.util">org.apache.ignite.ml.dataset.impl.cache.util</a></td>
 <td class="colLast">
 <div class="block">Contains util classes used in cache based implementation of dataset.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.dataset.impl.local">org.apache.ignite.ml.dataset.impl.local</a></td>
 <td class="colLast">
 <div class="block">Base package for local implementation of machine learning dataset.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.dataset.primitive">org.apache.ignite.ml.dataset.primitive</a></td>
 <td class="colLast">
 <div class="block">Package that contains basic primitives build on top of <a href="../../../../../org/apache/ignite/ml/dataset/Dataset.html" title="interface in org.apache.ignite.ml.dataset"><code>Dataset</code></a>.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.dataset.primitive.builder.context">org.apache.ignite.ml.dataset.primitive.builder.context</a></td>
 <td class="colLast">
 <div class="block">Contains partition <code>context</code> builders.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.dataset.primitive.builder.data">org.apache.ignite.ml.dataset.primitive.builder.data</a></td>
 <td class="colLast">
 <div class="block">Contains partition <code>data</code> builders.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.knn">org.apache.ignite.ml.knn</a></td>
 <td class="colLast">
 <div class="block">Contains main APIs for kNN algorithms.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.knn.ann">org.apache.ignite.ml.knn.ann</a></td>
 <td class="colLast">
 <div class="block">Contains main APIs for ANN classification algorithms.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.knn.classification">org.apache.ignite.ml.knn.classification</a></td>
 <td class="colLast">
 <div class="block">Contains main APIs for kNN classification algorithms.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.knn.regression">org.apache.ignite.ml.knn.regression</a></td>
 <td class="colLast">
 <div class="block">Contains helper classes for kNN regression algorithms.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.knn.utils">org.apache.ignite.ml.knn.utils</a></td>
 <td class="colLast">
 <div class="block">Contains util functionality for kNN algorithms.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.math.isolve.lsqr">org.apache.ignite.ml.math.isolve.lsqr</a></td>
 <td class="colLast">
 <div class="block">Contains LSQR algorithm implementation.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.multiclass">org.apache.ignite.ml.multiclass</a></td>
 <td class="colLast">
 <div class="block">Contains various multi-classifier models and trainers.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.naivebayes.compound">org.apache.ignite.ml.naivebayes.compound</a></td>
 <td class="colLast">
 <div class="block">Contains Compound naive Bayes classifier.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.naivebayes.discrete">org.apache.ignite.ml.naivebayes.discrete</a></td>
 <td class="colLast">
 <div class="block">Contains Bernoulli naive Bayes classifier.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.naivebayes.gaussian">org.apache.ignite.ml.naivebayes.gaussian</a></td>
 <td class="colLast">
 <div class="block">Contains Gaussian naive Bayes classifier.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.nn">org.apache.ignite.ml.nn</a></td>
 <td class="colLast">
 <div class="block">Contains neural networks and related classes.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.pipeline">org.apache.ignite.ml.pipeline</a></td>
 <td class="colLast">
 <div class="block">Contains Pipeline API.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.preprocessing">org.apache.ignite.ml.preprocessing</a></td>
 <td class="colLast">
 <div class="block">Base package for machine learning preprocessing classes.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.preprocessing.binarization">org.apache.ignite.ml.preprocessing.binarization</a></td>
 <td class="colLast">
 <div class="block">Contains binarization preprocessor.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.preprocessing.encoding">org.apache.ignite.ml.preprocessing.encoding</a></td>
 <td class="colLast">
 <div class="block">Contains encoding preprocessors.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.preprocessing.finalization">org.apache.ignite.ml.preprocessing.finalization</a></td>
 <td class="colLast">
 <div class="block">Contains vector finalization preprocessor.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.preprocessing.imputing">org.apache.ignite.ml.preprocessing.imputing</a></td>
 <td class="colLast">
 <div class="block">Contains Imputer preprocessor.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.preprocessing.maxabsscaling">org.apache.ignite.ml.preprocessing.maxabsscaling</a></td>
 <td class="colLast">
 <div class="block">Contains Max Abs Scaler preprocessor.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.preprocessing.minmaxscaling">org.apache.ignite.ml.preprocessing.minmaxscaling</a></td>
 <td class="colLast">
 <div class="block">Contains Min Max Scaler preprocessor.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.preprocessing.normalization">org.apache.ignite.ml.preprocessing.normalization</a></td>
 <td class="colLast">
 <div class="block">Contains Normalizer preprocessor.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.preprocessing.standardscaling">org.apache.ignite.ml.preprocessing.standardscaling</a></td>
 <td class="colLast">
 <div class="block">Contains Standard scaler preprocessor.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.recommendation">org.apache.ignite.ml.recommendation</a></td>
 <td class="colLast">
 <div class="block">Contains recommendation system framework.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.recommendation.util">org.apache.ignite.ml.recommendation.util</a></td>
 <td class="colLast">
 <div class="block">Contains util classes used in recommendation system framework.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.regressions.linear">org.apache.ignite.ml.regressions.linear</a></td>
 <td class="colLast">
 <div class="block">Contains various linear regressions.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.regressions.logistic">org.apache.ignite.ml.regressions.logistic</a></td>
 <td class="colLast">
 <div class="block">Contains various logistic regressions.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.selection.cv">org.apache.ignite.ml.selection.cv</a></td>
 <td class="colLast">
 <div class="block">Root package for cross-validation algorithms.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.selection.scoring.evaluator">org.apache.ignite.ml.selection.scoring.evaluator</a></td>
 <td class="colLast">
 <div class="block">Package for model evaluator classes.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.sql">org.apache.ignite.ml.sql</a></td>
 <td class="colLast">
 <div class="block">Contains util classes that help to work with machine learning models in SQL and train models on data from SQL tables.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.structures.partition">org.apache.ignite.ml.structures.partition</a></td>
 <td class="colLast">
 <div class="block">Contains internal APIs for dataset partitioned labeled datasets.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.svm">org.apache.ignite.ml.svm</a></td>
 <td class="colLast">
 <div class="block">Contains main APIs for SVM(support vector machines) algorithms.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.trainers">org.apache.ignite.ml.trainers</a></td>
 <td class="colLast">
 <div class="block">Contains model trainers.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.trainers.transformers">org.apache.ignite.ml.trainers.transformers</a></td>
 <td class="colLast">
 <div class="block">Various upstream transformers.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.tree">org.apache.ignite.ml.tree</a></td>
 <td class="colLast">
 <div class="block">Root package for decision trees.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.tree.boosting">org.apache.ignite.ml.tree.boosting</a></td>
 <td class="colLast">
 <div class="block">Contains implementation of gradient boosting on trees.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.tree.data">org.apache.ignite.ml.tree.data</a></td>
 <td class="colLast">
 <div class="block">Contains data and data builder required for decision tree trainers built on top of partition based dataset.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.tree.leaf">org.apache.ignite.ml.tree.leaf</a></td>
 <td class="colLast">
 <div class="block">Root package for decision trees leaf builders.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.tree.randomforest">org.apache.ignite.ml.tree.randomforest</a></td>
 <td class="colLast">
 <div class="block">Contains random forest implementation classes.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.tree.randomforest.data.impurity">org.apache.ignite.ml.tree.randomforest.data.impurity</a></td>
 <td class="colLast">
 <div class="block">Contains implementation of impurity computers based on histograms.</div>
 </td>
 </tr>
 <tr class="rowColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.tree.randomforest.data.statistics">org.apache.ignite.ml.tree.randomforest.data.statistics</a></td>
 <td class="colLast">
 <div class="block">Contains implementation of statistics computers for Random Forest.</div>
 </td>
 </tr>
 <tr class="altColor">
 <td class="colFirst"><a href="#org.apache.ignite.ml.util.generators">org.apache.ignite.ml.util.generators</a></td>
 <td class="colLast">
 <div class="block">Contains utility classes for data streams generation.</div>
 </td>
 </tr>
 </tbody>
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 <caption><span>Classes in <a href="../../../../../org/apache/ignite/ml/dataset/package-summary.html">org.apache.ignite.ml.dataset</a> used by <a href="../../../../../org/apache/ignite/ml/clustering/gmm/package-summary.html">org.apache.ignite.ml.clustering.gmm</a></span><span class="tabEnd">&nbsp;</span></caption>
 <tr>
 <th class="colOne" scope="col">Class and Description</th>
 </tr>
 <tbody>
 <tr class="altColor">
 <td class="colOne"><a href="../../../../../org/apache/ignite/ml/dataset/class-use/DatasetBuilder.html#org.apache.ignite.ml.clustering.gmm">DatasetBuilder</a>
 <div class="block">A builder constructing instances of a <a href="../../../../../org/apache/ignite/ml/dataset/Dataset.html" title="interface in org.apache.ignite.ml.dataset"><code>Dataset</code></a>.</div>
 </td>
 </tr>
 </tbody>
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 <caption><span>Classes in <a href="../../../../../org/apache/ignite/ml/dataset/package-summary.html">org.apache.ignite.ml.dataset</a> used by <a href="../../../../../org/apache/ignite/ml/clustering/kmeans/package-summary.html">org.apache.ignite.ml.clustering.kmeans</a></span><span class="tabEnd">&nbsp;</span></caption>
 <tr>
 <th class="colOne" scope="col">Class and Description</th>
 </tr>
 <tbody>
 <tr class="altColor">
 <td class="colOne"><a href="../../../../../org/apache/ignite/ml/dataset/class-use/DatasetBuilder.html#org.apache.ignite.ml.clustering.kmeans">DatasetBuilder</a>
 <div class="block">A builder constructing instances of a <a href="../../../../../org/apache/ignite/ml/dataset/Dataset.html" title="interface in org.apache.ignite.ml.dataset"><code>Dataset</code></a>.</div>
 </td>
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 <tr>
 <th class="colOne" scope="col">Class and Description</th>
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 <td class="colOne"><a href="../../../../../org/apache/ignite/ml/dataset/class-use/DatasetBuilder.html#org.apache.ignite.ml.composition.bagging">DatasetBuilder</a>
 <div class="block">A builder constructing instances of a <a href="../../../../../org/apache/ignite/ml/dataset/Dataset.html" title="interface in org.apache.ignite.ml.dataset"><code>Dataset</code></a>.</div>
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