Highly Automated Machine Learning

Version 10 introduces a wide range of integrated machine learning capabilities, from highly automated functions like Predict and Classify to functions based on specific methods and diagnostics. The functions work on many types of data—including numerical, categorical, textual, and image—allowing everyone to perform state-of-the-art machine learning in a simple way. A wide range of tasks can be performed, such as text classification, image recognition, or classification from generic data.

Predict numerical and categorical variables.
Support of numerical, textual, image, and sound data.
Automatic model and parameter selection.
Automatic data preprocessing (missing-values imputation, normalization, feature selection, ...).
Measurement tools to assess prediction quality.

Support of various dataset formats.
Control over classifier/predictor characteristics (performance goals).
Control over the algorithm used: logistic regression, nearest neighbors, random forest, support vector machine, neural network, ...
Access to prediction probabilities.
Possibility to change decision goals (custom utility function).