HTM Studio allows you to test whether our Hierarchical Temporal Memory (HTM) algorithms will find anomalies in your data. With just one click, you can uncover anomalies other techniques cannot find in your numeric, time-series data, in minutes.
Skip the hassle of setting parameters. Discover anomalies with one click.
Add local CSV (comma-separated value) files quickly with no upload or privacy issues.
Run multiple data streams simultaneously and compare discovered anomalies.
Visualize and export your results.
Don’t have your own data readily available? Experiment with our pre-loaded datasets, and see how HTM can be applied to a variety of use cases.
Monitor machine sensors to detect failures before they occur.
Understand energy usage and adjust resources in a connected building.
Identify unusual patterns in direction or speed from a vehicle.
Identify network changes and potential server degradation.
To get the full HTM Studio experience, watch our short walk-through video.
Data imported into HTM Studio must be formatted to meet certain conditions. See requirements and watch our brief instructional videos to learn how to prepare your data.
Data imported into HTM Studio must be in CSV file format and meet the following conditions:
CSV files must contain data that has only been generated from one source. If you have multiple sources, you will need to split your data by source and into separate CSV files.
I am interested in integrating HTM technology into my application, what can I do next?
Contact Us to discuss adding HTM technology to your system and for licensing opportunities. You can also engage with our HTM open source community at http://numenta.org . There you will find all of our code, and learning resources to develop a project using HTM.
Is HTM Studio open source?
Yes, the source is available on our GitHub repository .
What are the supported platforms and versions?
We support Mac OS/X (versions Yosemite and El Capitan) and Windows (64-bit versions 7, 8 and 10).
What if I don’t have a date/time column in my file, can I still use HTM Studio?
You can create a mock column for date / time by numbering each row (for example: 0, 1, 2, 3) in your file and ensure you have a header row, with the mock column named “time”.
What data formats does HTM Studio accept?
HTM Studio only accepts CSV files that meet certain requirements, which can be found in the get started section.
What is aggregation and how does HTM Studio use it?
Aggregation refers to the process of combining multiple values over a given period of time. This can be very useful if you are collecting data at a high frequency or if you have noisy data. Aggregating can reduce the amount of noise and help the HTM model learn faster. HTM Studio determines whether and how much to aggregate the input records before feeding them into the HTM model.
How do I choose the best aggregation window?
The ideal aggregation window is one that allows you to aggregate as much as you can but not too much. There is no one-size-fits-all value, as aggregation is application-dependent. HTM Studio makes a good first guess with any data set, but getting the best aggregation possible requires knowledge about the application itself. HTM Studio defaults to an automated technique that determines a best-effort aggregation window for your data. However, you can change the value of the aggregation window (or choose to not aggregate the data at all) in “advanced settings” when you create a new model. For more information on how to change the aggregation window, click here.
Why do I get different results with different aggregation settings?
When you aggregate your data, you are changing the number of data points that HTM sees. In some cases, aggregating your data may cause you to miss anomalies and in other cases, it may help you find anomalies by tuning out noise. The goal is to aggregate your data as much as possible but not too much. You can experiment with different aggregation windows in HTM Studio to see how it changes your results. To see an example, click here.
What are the advanced settings for?
HTM Studio determines the optimal parameters for each Hierarchical Temporal Memory (HTM) model and in some cases, aggregates your data for analysis. You can see what these parameters are in the advanced settings. We recommend that you follow the determined parameters for the best possible analysis. However, you may modify these parameters by clicking the advanced settings. For example, you can change the aggregation method and period. Or you can also suppress data aggregation by disabling the check box. See question “What does aggregate my data mean?” for information on aggregating data.
What is the initial learning period?
HTM Studio begins to build models from the metric in your data immediately. During the initial learning period, the anomaly results are displayed as grey bars with the value “N/A” displayed in the chart area. Once a HTM model has enough data points to learn on, it will display anomalies indicated by green, yellow and red bars.
How does HTM Studio determine what is anomalous?
HTM Studio first learns patterns in your data and builds a model to predict what is likely to happen in the next CSV record. Based on these predictions, the HTM algorithm generates an anomaly score for each data point. If you would like to learn more about anomaly detection, please refer to our Science of Anomaly Detection White Paper .
Why am I not seeing any anomalies?
There are many reasons why this may occur, but some of the most common are:
Numenta is happy to license HTM Studio to you if you accept all of the terms and conditions contained in this Agreement. By accepting this agreement and downloading HTM Studio, you indicate that you have read and understand this Agreement and accept all of its terms and conditions. If you agree to these terms and conditions on behalf of a business, government agency, or other entity, you warrant that you have authority to bind that business, agency, or other entity to this Agreement, and your agreement to these terms and conditions will be treated as the agreement of that business, agency, or other entity. In that event, “you” and “your” refer herein to that business, agency, or other entity.
The purpose of this Preamble is to give a plain English description of this Agreement. Please read the rest of the Agreement carefully for detailed terms and conditions.
Numenta welcomes individuals, businesses, and other entities to explore and advance HTM technology. This license allows you to explore HTM ideas using HTM Studio in whole or in part, at no charge, as long as your work is for research and experimentation purposes only. You may not sell or distribute any portion of HTM Studio or your work product for commercial or production use unless you take an appropriate commercial license from us.
HTM Studio collects anonymized application activity statistics (clicks, menus opened, etc.) and reports them to Numenta so we can learn about the use of HTM Studio and continue to improve it. HTM Studio will never collect or report information about HTM Studio users (names, IP addresses, etc.) or users’ data (file names, data points, results, etc.).
“HTM Studio” refers to the application that can be used to find anomalies in streaming data. All HTM Studio code is made available through the “numenta” GitHub organization at http://github.com/numenta, under an AGPLv3 license.