Skip to main content

Release Notes for Machine Learning - Application

New AlteryxMachine Learning (AYX ML) Application features and capabilities are available to you automatically. Find out what's new.

August 10, 2023

Version 2023.26

New File Menu

Added a File menu to the Global Header that you can access while working on your Machine Learning project. Use the File menu to create a new project or select a recent project from a list. Note that the File menu replaces the All Projects button. To return to the Landing Page, select the Machine Learning logo next to the File menu.

June 13, 2023

Version 2023.22

Project Sessions

Use Sessions to create multiple versions of your ML project. Experiment with different settings to fine-tune your model for improved model performance. Sessions stores previous versions of your model so you can always revert back to an older version if needed.

May 31, 2023

Version 2023.15

ML Integration with Plans

Added integration with Plans. Use Plans to add new data from a workflow to an existing Machine Learning project. Learn more about ML integration with Plans.

Faster Data Insights

Runtime Upgrade Required

To use this feature, you must upgrade your project to AYX ML Runtime version 2.19.0.

Added the Correlations and Outliers panels from Data Insights to Problem Setup. You can nowquicklyview insights about your data before selecting a problem type.

May 4, 2023

Version 2023.13

Simplified Modeling Workflow

Reduced the number of modeling workflow stages.You can find the previous Model Setup and Feature Engineering options in the Auto Model stage.

Streamlined Model Evaluation

Redesigned the General tab to highlight metrics that drive business outcomes. Combined the Performance and Advanced Insights tabs to house all advanced metrics.

April 27, 2023

Version 2023.12

Time Series Prediction Intervals for All Models

Added prediction intervals for all Time Series models in the forecast graph. Additionally, the downloadable forecast CSV file includes the prediction intervals.

April 20, 2023

Version 2023.11

Python Model Export

Runtime Upgrade Required

To use this feature, you must upgrade your project to AYX ML Runtime version 2.16.0.

Added the option to export your model as Python code in the Export and Predict stage. Export your model to evaluate the underlying code.

April 6, 2023

Version 2023.09

New Landing Page

Renamed the Project Page to the Landing Page and updated the page design. Updates include a new page header, table styling, and a Machine Learning project icon. There is no change to existing functionality.

New Navigation to the Landing Page

Previously, selecting All Projects would navigate to the Project Page (now called the Landing Page). Now, select the Machine Learning icon in the upper-left corner of the page to navigate to the Landing Page.

Example Use Cases

Added a link to Example Use Cases in AYX ML to the Additional Resources section of the Resources Pane. You can find the Resources Pane on the new Landing Page.

March 30, 2023

Version 2023.08

New Problem Setup Stage

Streamlined the data prep and model selection process. You can now easily see your data and choose a machine learning method at the same time. Problem Setup replaces the Data Prep stage.

Time Series Prediction Intervals

Added prediction intervals to Arima, Prophet, and Exponential Smoothing model types.To view the prediction intervals, go to the Time Series Forecast Graph located in the Export and Predict stage. Use prediction intervals to determine the confidence of a forecasted data point.

February 9, 2023

Version 2023.02

Manage Columns

You can now easily select the columns you want to include in the modeling process and change column data types. To use this feature, select Manage Columns in the Prep Data stage.

January 31, 2023

Version 2023.01

Runtime Upgrade Required

To use these features, you must upgrade your project to AYX ML Runtime version 2.4.1.

Data and Feature Anomaly Checks Added to Export and Predict

Added a message to inform you if your data for prediction contains categorical values that were not present in your training data. The message details what those values are, and which columns contain them.

Customizable Feature Selection

Added the ability to select which features you use in your model. This includes engineered features.To customize your feature selection, go to the Features tab in the Feature Engineering step. Reducing your feature count can speed up the modeling process.

Partial Dependence Plot Performance Improvements

Improved the speed of populating the Partial Dependence plot. On average, you can expect 50% faster load times.

December 8, 2022

Version 2022.41

Runtime Versioning

Added the ability to upgrade individual projects to the latest AYX ML Runtime Version—and to revert back to your most recent version if you change your mind. You can find this functionality in the 3-dot menu on each project on the project page.

  • Project versioning ensures that changes to modeling algorithms DO NOT impact business results unless you select an upgrade. This provides a consistent experience when you revisit a previous project.

  • Note that the AYX ML Runtime Version upgrade only applies to model tuning improvements made by Alteryx. Improvements to the UX, new features, security, and infrastructure update automatically.

December 1, 2022

Version 2022.40

Time Series Enhancements

What Is Time Series

Time Series regression expands your modeling capabilities with data that includes a time component. Now, you can forecast into the future and get accurate predictions. Do things like demand forecasting, financial forecasting, and more with Alteryx Machine Learning.

Alteryx Machine Learning uses commonly used and state-of-the-art time series models. These include Facebook Prophet, ARIMA, and ETS, in addition to other regression models such as XGBoost and LightGBM.

Why Time Series Matters

Use Time Series for future-looking, time-based predictions. This empowers you to quickly leverage prior data to forecast future outcomes. Enhanced capabilities account for trending and seasonality, making model performance stronger.

New Functionality

Time Series now includes 2 major enhancements to the Machine Learning experience:

  • Decomposition [Model Setup step]: Visualize trend and seasonal signals in isolation from the residual signal. This allows the non-time series specific models to perform better in most cases (where time-series specific models are Facebook Prophet, ARIMA, and ETS). We run all models with and without decomposition and then display the best model on the leaderboard. We support Decomposition Visualizations for these frequencies:

  • Hourly

  • Daily

  • Weekly

  • Monthly

  • Quarterly

  • Time Series Forecast Graph and Data Export [Export and Predict step]: Introduced line graph and graph data to visualize and then use forecasted data.

Changes to Existing Workflow

For a clearer workflow, we moved items from Data Insights to a new Model Setup step. Note that this doesn’t represent new functionality, just a new organizational flow.

August 25, 2022

Version 2022.28

Feature Engineering Step

Added an automated Feature Engineering step to Alteryx Machine Learning. This step allows you to apply primitives (generalized operations) to calculate new features. These features can improve model performance and help you gain further insight. Additionally, you can view the correlation values for the engineered features. Look for this new feature on the left side of the Alteryx Machine Learning interface.

August 2, 2022

Version 2022.25

Updated Integer Parsing

We extended support for parsing real numbers (for example, 2.45 and 3.0) as integers. The parsing truncates the right side of the decimal point. For example, 2.45 becomes 2, and 3.0 becomes 3.

New Time Series Primitives

Added "Fourier Transform" and "Rolling Trend" primitives for improved Time Series feature engineering. We also added an additional 16 DateTime primitives for feature engineering.

Custom Input for DateTime Formats

Added 20 new DateTime formats and the ability to enter your own custom format. You can now use more DateTime datasets with our Time Series Regression model.

Machine Learning Predict Tool—Data Validation for Time Series Models

Added Time Series data validation to the Machine Learning Predict tool in Designer. The data validation checks if your input data length is longer than the forecast horizon.

Correlation Tab—Switch X-Y Axes on 2-Variable Plot

Added an option to switch the axes of the 2-Variable Plot in the Correlations tab.

July 21, 2022

Version 2022.24

Pipeline Highlights

Expanded Pipeline Highlights in the Auto Model leaderboard for categorical and numerical operations. We now sort operations by order of execution in the model pipeline. Use this information to choose a model based on which operations we use in the model.

June 23, 2022

Version 2022.20

Time Series—Irregularly Spaced Data

Support added for irregularly spaced Time Series datasets.

Time Series—Data Checks

Added data checks to warn you when we modify your data.

June 16, 2022

Version 2022.19

Stop Criteria—Model Setup

You now have the option to set "time" as the stop criteria for model search completion. The minimum stop time is 1 minute.

April 18, 2022

Version 2022.12

Facebook® Prophet Estimator

Added Prophet to improve predictions for Time Series Regression models. This addition targets datasets with trends and seasonality.

ARIMA Regressor

Added ARIMA Regressor for Time Series Regression. ARIMA is a high performant statistical algorithm for Time Series datasets.

Select Completed Models

Updated the Stop button in the Auto Model search step. You can now stop the model search and select completed models up to that point.

Features Visibility

Updated the Features panel in the Auto Model step to show all features contributing to your model. This helps you understand and evaluate models based on the features in use. In addition, features used in ensemble models are also shown.

March 17, 2022

Version 2022.08

Unary Column Detection

A new data check identifies unary data type columns and automatically recommends next steps. This enables you to quickly detect columns to exclude from Machine Learning. The No Variance Data Check flags columns that contain only 1 unique value and then provides you with a recommendation to drop those columns.

February 2, 2022

Version 2022.03

Alteryx Machine Learning is now available!