The Google code team today announced that its Google Prediction API was leaving “Labs” status with some new features for developers to utilize.

Google Prediction API launched to makes apps smarter by continually learning and adapting to changing conditions with one single line of code.

The team had this to say on its blog:

Since the general availability launch of the Prediction API this year at Google I/O, we have been working hard to give every developer access to machine learning in the cloud to build smarter apps. We’ve also been working on adding new features, accuracy improvements, and feedback capability to the API. Today we take another step by announcing Prediction v1.4. With the launch of this version, Prediction is graduating from Google Code Labs, reflecting Google’s commitment to the API’s development and stability.

As the team notes, when a feature or API leaves “Labs” status, it means that Google is sticking with the service long-term, and apparently this particular learning API has been widely used by developers since it was announced at Google I/O.

The new features in Version 1.4 include:

Data Anomaly Analysis

One of the hardest parts of building an accurate predictive model is gathering and curating a high quality data set. With Prediction v1.4, we are providing a feature to help you identify problems with your data that we notice during the training process. This feedback makes it easier to build accurate predictive models with proper data.

PMML Import

PMML has become the de facto industry standard for transmitting predictive models and model data between systems. As of v1.4, the Google Prediction API can programmatically accept your PMML for data transformations and preprocessing.

The PMML spec is vast and covers many, many features. You can find more details about the specific features that the Google Prediction API supports here.

The team also included this tutorial video about the Google Prediction API: