Use automated machine learning and best practices to build predictive models in 4 clicks now on your desktop or in your browser

Guided data prep

Start by loading your data and selecting an outcome, like making a prediction, identifying clusters, or finding outliers. You can select any type of data, from any location. Auto Model will apply data science best practices based on the type of data you select.

Auto Model will automatically analyze your data to identify common quality problems like correlations, missing values, and stability.

Guided Data Prep
Automated Model Selection

Automated model selection and optimization

RapidMiner Auto Model suggests the best Machine Learning techniques for your data and determines the optimal parameters for your models. Auto Model uses correct model validation to ensure the highest possible confidence in the results.

Select from a variety of machine learning algorithms including Native Bayes, Logistic Regression, Deep Learning, Random Forest, and Gradient Boosted Trees (XGBoost).

Turn predictive models into prescriptive actions

Auto Model allows you to explain individual predictions and to visually or algorithmically “what if” and optimize for specific outcomes. The advanced results dashboard allows you deep-dive into key model metrics and quickly find the optimal model for your data.

Using the model simulator in Auto Model allows you to determine the specific actions to take in order to achieve the desired outcome predicted by the model.

results-insights
no-black-boxes

No black boxes here

Other products that use automated machine learning hide the workings of the model from the data scientist and analyst, making it difficult or even impossible to really understand how the model works.

The output from Auto Model is a RapidMiner Studio process, so you can instantly visualize all the data prep and modeling steps, and selectively fine tune and test them as needed.

#noblackboxes

Get started with RapidMiner Auto Model

Here’s RapidMiner Auto Model in Action