markdown stringlengths 44 160k | filename stringlengths 3 39 |
|---|---|
---
title: Platform home
description: Access the full DataRobot UI documentation, including feature descriptions for the UI and API, data preparation, tutorials, and a glossary.
---
# DataRobot UI documentation
The **UI docs** tab describes workflow and reference material for the UI version of the DataRobot AI Platf... | index |
---
title: ELI5
description: Explain it Like I'm 5 provides a list with brief, easily digestible answers. Answers links to more complete documentation.
---
# ELI5 {: #eli5 }
Explain it like I'm 5 (ELI5) contains complex DataRobot and data science concepts, broken down into brief, digestible answers. Many topics inclu... | eli5 |
---
title: Learn more
description: Get started in DataRobot with descriptions of common terms and concepts, as well as how-tos.
---
# Learn more {: #learn-more }
This page provides access to learning resources that help you get started in DataRobot, including simplified explanations of concepts, how-tos and end-to-en... | index |
---
title: MLOps
description: DataRobot machine learning operations (MLOps) provides a central hub for you to deploy, monitor, manage, and govern your models in production.
---
# MLOps {: #mlops }
DataRobot MLOps provides a central hub to deploy, monitor, manage, and govern all your models in production. You can dep... | index |
---
title: MLOps FAQ
dataset_name: N/A
description: Provides a list, with brief answers, of frequently asked MLOps deployment and monitoring questions. Answers link to complete documentation.
domain: mlops
expiration_date: 10-10-2024
owner: nick.aylward@datarobot.com
url: docs.datarobot.com/docs/mlops/mlops-faq.html
-... | mlops-faq |
---
title: Platform
description: This section includes information and links for managing user settings; authentication and SSO; the administrator's guide; sharing and permissions; user documentation for companion tools; and more.
---
# Platform {: #platform }
The platform section provides materials for users and adm... | index |
With the **Comments** link, you can add comments to—even host a discussion around—any item in the catalog that you have access to. Comment functionality is available in the **AI Catalog** (illustrated below), and also as a model tab from the Leaderboard and in use case tracking. With comments you can:
* Ta... | comm-add |
??? note "Dataset requirements for time series batch predictions"
To ensure DataRobot can process your time series data, configure the dataset to meet the following requirements:
* Sort prediction rows by their timestamps, with the earliest row first.
* For multiseries, sort prediction rows by series ID an... | batch-pred-ts-scoring-data-requirements |
!!! note "DataRobot fully supports the latest version of Google Chrome"
Other browsers such as Edge, Firefox, and Safari are not fully supported. As a result, certain features may not work as expected. DataRobot recommends using Chrome for the best experience. Ad block browser extensions may cause display or perfo... | browser-compatibility |
The **Clustering** tab sets the number of clusters that DataRobot will find during Autopilot. The default number of clusters is based on number of series in the dataset.
To set the number, add or remove values from the entry box and select the value from the dropdown:
Note that wh... | ts-cluster-adv-opt-include |
There are several options available in the **Actions** menu, which can be accessed for each model package in the **Model Packages** tab of the **Model Registry**:
The available options depend on a variety of criteria, including user permissions and the data available to your model package... | manage-model-packages |
??? faq "How does DataRobot track drift?"
For data drift, DataRobot tracks:
* **Target drift**: DataRobot stores statistics about predictions to monitor how the distribution and values of the target change over time. As a baseline for comparing target distributions, DataRobot uses the distribution of predictio... | how-dr-tracks-drift-include |
## Deep dive: Imbalanced targets {: #deep-dive-imbalanced-targets }
In AML and Transaction Monitoring, the SAR rate is usually very low (1%–5%, depending on the detection scenarios); sometimes it could be even lower than 1% in extremely unproductive scenarios. In machine learning, such a problem is called _class imbal... | aml-4-include |
* Frozen thresholds are not supported.
* Blenders that contain monotonic models do not display the MONO label on the Leaderboard for OTV projects.
* When previewing predictions over time, the interval only displays for models that haven’t been retrained (for example, it won’t show up for models with the **Recommended... | dt-consider |
| | Element | Description |
|---|---|---|
|  | Filter by predicted or actual | Narrows the display based on the predicted and actual class values. See [Filters](#filters) for details.|
|  | Show color overlay | Sets whether to display the activation map in either black and ... | activation-map-include |
Consider the following when working with segmented modeling deployments:
* Time series segmented modeling deployments do not support data drift monitoring.
* Automatic retraining for segmented deployments that use clustering models is disabled; retraining must be done manually.
* Retraining can be triggered by ac... | deploy-combined-model-include |
The **Histogram** chart is the default display for numeric features. It "buckets" numeric feature values into equal-sized ranges to show frequency distribution of the variable—the target observation (left Y-axis) plotted against the frequency of the value (X-axis). The height of each bar represents the number of ... | histogram-include |
## Business problem {: #business-problem }
A key pillar of any AML compliance program is to monitor transactions for suspicious activity. The scope of transactions is broad, including deposits, withdrawals, fund transfers, purchases, merchant credits, and payments. Typically, monitoring starts with a rules-based syste... | aml-1-include |
Data integrity and quality are cornerstones for creating highly accurate predictive models. These sections describe the tools and visualizations DataRobot provides to ensure that your project doesn't suffer the "garbage in, garbage out" outcome.
| data-description |
### Business problem {: #business-problem }
A "readmission" event is when a patient is readmitted into the hospital within 30 days of being discharged. Readmissions are not only a reflection of uncoordinated healthcare systems that fail to sufficiently understand patients and their conditions, but they are also a tre... | hospital-readmit-include |
## DRUM on Windows with WSL2 {: #drum-on-windows-with-wsl2 }
DRUM can be run on Windows 10 or 11 with WSL2 (Windows Subsystem for Linux), a native extension that is supported by the latest versions of Windows and allows you to easily install and run Linux OS on a Windows machine. With WSL, you can develop custom tasks... | drum-for-windows |
| | Element | Description |
|--|---------|-------------|
|  | Include input features | Writes input features to the prediction results file alongside predictions. To add specific features, enable the **Include input features** toggle, select **Specific features**, and ty... | prediction-options-include |
Log in to GitHub before accessing these GitHub resources.
| github-sign-in-plural |
## About final models {: #about-final-models }
The original ("final") model is trained without holdout data and therefore does not have the most recent data. Instead, it represents the first backtest. This is so that predictions match the insights, coefficients, and other data displayed in the tabs that help evaluate ... | date-time-include-5 |
## Troubleshooting {: #troubleshooting }
Problem | Solution | Instructions
---------- | ----------- | ---------------
When attempting to execute an operation in DataRobot, the firewall requests that you clear the IP address each time. | Add all whitelisted IPs for DataRobot. | See [Source IP addresses for w... | data-conn-trouble |
DataRobot detects the date and/or time format (<a target="_blank" href="https://docs.python.org/2/library/datetime#strftime-and-strptime-behavior">standard GLIBC strings</a>) for the selected feature. Verify that it is correct. If the format displayed does not accurately represent the date column(s) of your dataset, mo... | date-time-include-1 |
| | Element | Description |
|---|---|---|
|  | Selected word | Displays details about the selected word. (The term *word* here equates to an [*n-gram*](glossary/index#ngram), which can be a sequence of words.) <br><br>Mouse over a word to select it. Words that appear more frequently display in a ... | word-cloud-include |
??? info "Category Cloud availability"
The **Category Cloud** insight is available on the **Models > Insights** tab and on the **Data** tab. On the **Insights** page, you can compare word clouds for a project's categorically-based models. From the **Data** page you can more easily compare clouds across features. No... | category-cloud-include |
## Predict and deploy {: #predict-and-deploy }
Once you identify the model that best learns patterns in your data to predict SARs, you can deploy it into your desired decision environment. *Decision environments* are the ways in which the predictions generated by the model will be consumed by the appropriate organizat... | aml-3-include |
Log in to GitHub before clicking this link.
| github-sign-in |
??? note "Time series blueprints with Scoring Code support"
<span id="ts-sc-blueprint-support">The following blueprints typically support Scoring Code:</span>
* AUTOARIMA with Fixed Error Terms
* ElasticNet Regressor (L2 / Gamma Deviance) using Linearly Decaying Weights with Forecast Distance Modeling
... | scoring-code-consider-ts |
No-Code AI Apps allow you to build and configure AI-powered applications using a no-code interface to enable core DataRobot services without having to build models and evaluate their performance in DataRobot. Applications are easily shared and do not require users to own full DataRobot licenses in order to use them. Ap... | no-code-app-intro |
The **Over time** chart helps you identify trends and potential gaps in your data by displaying, for both the original modeling data and the derived data, how a feature changes over the primary date/time feature. It is available for all time-aware projects (OTV, single series, and multiseries). For time series, it is a... | date-time-include-4 |
### Business problem {: #business-problem }
Because, on average, it takes roughly 20 days to process an auto insurance claim (which often frustrates policyholders), insurance companies look for ways to increase the efficiency of their claims workflows. Increasing the number of claim handlers is expensive, so companies... | fraud-claims-include |
The execution environment limit allows you to control how many custom model environments a user can add to the [Custom Model Workshop](custom-model-workshop/index). In addition, the execution environment _version_ limit allows you to control how many versions a user can add to _each_ of those environments. These limits... | ex-env-limits |
## Feature considerations {: #feature-considerations }
Consider the following when working with Scoring Code:
* Using Scoring Code in production requires additional development efforts to implement model management and model monitoring, which the DataRobot API provides out of the box.
* Exportable Java Scoring Code ... | scoring-code-consider |
!!! note
Some [DataRobot University](https://university.datarobot.com){ target=_blank } courses require subscriptions.
| dru-subscription |
The [metrics values](#metrics-explained) on the ROC curve display might not always match those shown on the Leaderboard. For ROC curve metrics, DataRobot keeps up to 120 of the calculated thresholds that best represent the distribution. Because of this, minute details might be lost. For example, if you select **Maximiz... | max-metrics-roc |
## Time-aware models on the Leaderboard {: #time-aware-models-on-the-leaderboard }
Once you click **Start**, DataRobot begins the model-building process and returns results to the Leaderboard.
!!! note
Model parameter selection has not been customized for date/time-partitioned projects. Though automatic parameter... | date-time-include-3 |
End of preview. Expand in Data Studio
README.md exists but content is empty.
- Downloads last month
- 163