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Machine Learning components

tALSModel Generates an user-ranking-product associated matrix, based on given user-product interactive data.
tClassify Predicts which class an element belongs to, based on the classifier model generated by a model training component.
tClassifySVM Predicts which class an element belongs to, based on the classifier model generated by tSVMModel.
tDecisionTreeModel Analyzes feature vectors usually prepared and provided by tModelEncoder to generate a classifier model that is used by tPredict to classify given elements.
tGradientBoostedTreeModel Analyzes feature vectors usually prepared and provided by tModelEncoder to generate a classifier model that is used by tPredict to classify given elements.
tKMeansModel Analyzes incoming datasets based on applying the K-Means algorithm.
tKMeansStrModel Analyzes incoming datasets in near real-time, based on applying the K-Means algorithm.
tLinearRegressionModel Builds a linear regression model using a training dataset.
tLogisticRegressionModel Analyzes feature vectors usually pre-processed by tModelEncoder to generate a classifier model that is used by tPredict to classify given elements.
tMahoutClustering (deprecated) Groups unlabeled numerical data into clusters that can reveal interesting patterns or helps identifying abnormal data items in the data set.
tModelEncoder Performs featurization operations to transform data into the format expected by the model training components such as tLogisticRegressionModel or tKMeansModel.
tNaiveBayesModel Generates a classifier model that is used by tPredict to classify given elements.
tPredict Predicts the situation of an element.
tPredictCluster Predicts the cluster of an element.
tRandomForestModel Analyzes feature vectors.
tRecommend Recommends products to users known to this model, based on the user-product recommender model generated by tASLModel.
tSVMModel Generates an SVM-based classifier model that can be used by tPredict to classify given elements.

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