Machine Learning / Initialize Model

 

Updated: July 2, 2015

Azure Machine Learning Studio provides many different state-of-the art machine learning algorithms to help you build analytical models.

First, identify the general type of machine learning task you are performing, as the algorithms grouped in each category are tailored to specific predictive tasks.

If you need help selecting an algorithm, see these resources:

After you have chosen an algorithm and configured its parameters, you can then use one of the training modules to run data through the chosen algorithms, or you can use Tune Model Hyperparameters to iterate over all possible parameters and determine the optimal configuration for your task and data.

Having built and trained a model, typically your next step is to use one of the Machine Learning / Score modules to generate predictions based on the model.

You can use the modules in the Machine Learning / Evaluate section to measure the accuracy of the model, based on the scores you’ve generated.

Azure Machine Learning Studio provides the following broad kinds of machine learning algorithms, grouped by typical machine learning scenarios.

Category

Anomaly Detection

Classification

Clustering

Regression

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