`distributed`

¶

## Classifier¶

`logistic_classifier.submit_training_job` |
Submit a job to create a `LogisticClassifier` (using logistic regression as a classifier) to predict the class of a discrete target variable (binary or multiclass) based on a model of class probability as a logistic function of a linear combination of the features. |

`svm_classifier.submit_training_job` |
Submit job to create a `SVMClassifier` to predict the class of a binary target variable based on a model of which side of a hyperplane the example falls on. |

`boosted_trees_classifier.submit_training_job` |
Submit a job to create a (binary or multi-class) classifier model of type `BoostedTreesClassifier` using gradient boosted trees (sometimes known as GBMs). |

`random_forest_classifier.submit_training_job` |
Submit a job to create a (binary or multi-class) classifier model of type `RandomForestClassifier` using an ensemble of decision trees trained on subsets of the data. |

## Regression¶

`linear_regression.submit_training_job` |
Submit a job to create a `LinearRegression` to predict a scalar target variable as a linear function of one or more features. |

`boosted_trees_regression.submit_training_job` |
Submit a job to create a `BoostedTreesRegression` to predict a scalar target variable using one or more features. |

`random_forest_regression.submit_training_job` |
Submit a job to create a `RandomForestRegression` to predict a scalar target variable using one or more features. |

## Graph Analytics¶

`pagerank.submit_training_job` |
Submit job to compute the PageRank for each vertex in the graph. |

`label_propagation.submit_training_job` |
Given a weighted graph with observed class labels of a subset of vertices, infer the label probability for the unobserved vertices using the “label propagation” algorithm. |

## Job Management¶

`_dml_job_status.DMLJobStatus` |
DMLJobStatus tracks a distributed machine learning job while it is running on a cluster. |