Why use feature datasets

Got something to say? Cancel reply Enter your comment here Fill in your details below or click an icon to log in:. Email required Address never made public. Name required. Follow Following. Esri Australia Technical Blog Join other followers. All feature classes in a feature dataset must share a common coordinate system, and the x,y coordinates of their features should fall within a common spatial extent.

When you create a feature class in an existing feature dataset, the coordinate system is inherited from the feature dataset. See An overview of spatial references for information on defining the coordinate system and spatial reference. The Create Feature Dataset geoprocessing tool opens. Feedback on this topic? Back to Top. The Shape Files option is used to load from a shape files. Choose the Database option and click on the folder icon next to the Feature Datastore Path field.

This will open the Find Geodatabase window. Squared hinge. Focal loss. Run a model. Before running a model. The Run settings section. Batch size. The Run button. Early stopping. Why use early stopping. How to use early stopping. Optimization principles in deep learning. Optimization with labeled training. Model loss. Learning rate schedule. Optimizer test with Rosenbrock function.

How optimizers behave at a saddle point. Stochastic gradient descent. Experiment states. Created state. Queued state. Running state. Paused state. Completed state. Failed state. Dequeued state.

Improve your model. Change run settings. Change block parameters. Continue experimenting. Several ways to continue with an experiment. Tips on how to improve an experiment. Link to parent experiment. Duplicate experiment. Other ways to continue experimenting. How to duplicate an experiment. Iterate experiment. Continue training. Reuse part of model. Tune experiment. Copy blocks with weights to another model. Multiple inputs. Transfer learning. Trainable or non-trainable. Image augmentation.

How to use image augmentation. Search and filter for experiments. Experiment tagging. How to use tags in the experiment search. Information pop-up. Modeling canvas controls. Controls to navigate the Modeling canvas. Evaluation view elements. Loss and metrics. Navigating the loss and metrics plot. How to read the loss curve. Predictions inspection. Select the subset and checkpoint to inspect. Select the label to inspect. Predictions table. Confusion matrix.

Interact with the confusion matrix. How to improve classification results. Multi-dimensional target. Scatter plot. Interact with the scatter plot.

How to improve regression results. ROC Curve. How to read the ROC curve. Interact with the ROC curve. How to decide on a threshold. Classification loss metrics. Loss curve. Binary accuracy. Suggestions on how to improve. Categorical accuracy. Binary error. Categorical error.

AUC explained. Macro F1-score. Micro F1-score. Intersection over union. When is intersection over union available. What's the intersection over union. Exact match ratio. When is exact match ratio available. What's the exact match ratio. Regression loss metrics. Why use MAE. When to use MAE. Example of use. Why use MSE. When to use MSE. When to use RMSE. When to use R-squared. Measure performance when working with imbalanced data.

Evaluate on macro-precision, -recall, and -F1. Evaluate with the confusion matrix. Enable deployment for requests. API information. Deployment web app. Monitoring deployment. Monitoring graphs. Deploy to API limitations. Unsupported deployment scenarios. Request size. Input data. Search and filter deployed experiments. Peltarion connectors. No-code connectors for productivity apps.

Model download. Downloading the model. Utility functions. Model download for MLflow. Deploy a MLflow Server. Get a prediction from the server. Model download for UIPath. Model download for TF serving. Deploy a TF Serving server. Get predictions from the server. AI for Sheets. How to install Peltarion AI for Sheets. How to use Peltarion AI for Sheets. AI for Excel. How to install Peltarion AI for Excel. How to use Peltarion AI for Excel. PowerApps connector. How to use Peltarion with Power Apps.

Bubble connector. Peltarion plugins. Bubble plugin for text similarity. Bubble plugin for classification and regression. Install the Bubble plugin. Create a workflow. Zapier connector. How to use Peltarion with Zapier. Working Zap examples. Test with Postman. Available how-tos. Test image similarity deployment. Deploy an experiment.

Configure Postman. Manage environment. Test your deployment with an image. Show results. Data API. Enabling the Data API. How to upload files. Deployment API. OpenAPI specification.

Structure of a prediction request. Deployment API in Python. How to use sidekick. Working with responses. Similarity API. Structure of a similarity request. Similarity API in Python.