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#Org.apache.spark.ml.classification Classes and Interfaces - 25 results found.
| Name | Description | Type | Package | Framework |
| BinaryLogisticRegressionSummary | Binary Logistic regression results for a given model. | Class | org.apache.spark.ml.classification | Apache Spark |
| BinaryLogisticRegressionTrainingSummary | Logistic regression training results. | Class | org.apache.spark.ml.classification | Apache Spark |
| ClassificationModel | Model produced by a Classifier. | Class | org.apache.spark.ml.classification | Apache Spark |
| Classifier | Single-label binary or multiclass classification. | Class | org.apache.spark.ml.classification | Apache Spark |
| DecisionTreeClassificationModel | Decision tree model for classification. | Class | org.apache.spark.ml.classification | Apache Spark |
| DecisionTreeClassifier | Decision tree learning algorithm for classification. | Class | org.apache.spark.ml.classification | Apache Spark |
| GBTClassificationModel | Gradient-Boosted Trees (GBTs) model for classification. | Class | org.apache.spark.ml.classification | Apache Spark |
| GBTClassifier | Gradient-Boosted Trees (GBTs) learning algorithm for classification. | Class | org.apache.spark.ml.classification | Apache Spark |
| LabelConverter | Label to vector converter. | Class | org.apache.spark.ml.classification | Apache Spark |
| LogisticAggregator | LogisticAggregator computes the gradient and loss for binary logistic loss function, as used in binary classification for instances in sparse or dense vector in a online fashion. | Class | org.apache.spark.ml.classification | Apache Spark |
| LogisticCostFun | LogisticCostFun implements Breeze's DiffFunction[T] for a multinomial logistic loss function, as used in multi-class classification (it is also used in binary logistic regression). | Class | org.apache.spark.ml.classification | Apache Spark |
| LogisticRegression | Logistic regression. | Class | org.apache.spark.ml.classification | Apache Spark |
| LogisticRegressionModel | Model produced by LogisticRegression. | Class | org.apache.spark.ml.classification | Apache Spark |
| LogisticRegressionSummary | Abstraction for Logistic Regression Results for a given model. | Interface | org.apache.spark.ml.classification | Apache Spark |
| LogisticRegressionTrainingSummary | Abstraction for multinomial Logistic Regression Training results. | Interface | org.apache.spark.ml.classification | Apache Spark |
| MultilayerPerceptronClassificationModel | Classification model based on the Multilayer Perceptron. | Class | org.apache.spark.ml.classification | Apache Spark |
| MultilayerPerceptronClassifier | Classifier trainer based on the Multilayer Perceptron. | Class | org.apache.spark.ml.classification | Apache Spark |
| NaiveBayes | Naive Bayes Classifiers. | Class | org.apache.spark.ml.classification | Apache Spark |
| NaiveBayesModel | Model produced by NaiveBayes param: pi log of class priors, whose dimension is C (number of classes) | Class | org.apache.spark.ml.classification | Apache Spark |
| OneVsRest | Reduction of Multiclass Classification to Binary Classification. | Class | org.apache.spark.ml.classification | Apache Spark |
| OneVsRestModel | Model produced by OneVsRest. | Class | org.apache.spark.ml.classification | Apache Spark |
| ProbabilisticClassificationModel | Model produced by a ProbabilisticClassifier. | Class | org.apache.spark.ml.classification | Apache Spark |
| ProbabilisticClassifier | Single-label binary or multiclass classifier which can output class conditional probabilities. | Class | org.apache.spark.ml.classification | Apache Spark |
| RandomForestClassificationModel | Random Forest model for classification. | Class | org.apache.spark.ml.classification | Apache Spark |
| RandomForestClassifier | Random Forest learning algorithm for It supports both binary and multiclass labels, as well as both continuous and categorical | Class | org.apache.spark.ml.classification | Apache Spark |