![]() ![]() For example, if your source dataset has numbers handled as text, you must change them to a numeric data type before using math operations. You might need to change the data type for certain operations. Select the Data type option if you need to assign a different data type to the selected columns. You can choose columns individually by name or index, or you can choose a group of columns by type. You can find the component in the Data Transformation category.Ĭlick Edit column in the right panel of the component and choose the column or set of columns to work with. In Azure Machine Learning designer, add the Edit Metadata component to your pipeline and connect the dataset you want to update. For example, some components work only with specific data types or require flags on the columns, such as IsFeature or IsCategorical.Īfter you perform the required operation, you can reset the metadata to its original state. Use Edit Metadata anytime you need to modify the definition of a column, typically to meet requirements for a downstream component. Indicating which column contains the class label or contains the values you want to categorize or predict.Ĭhanging date/time values to numeric values or vice versa. Treating Boolean or numeric columns as categorical values. The value and data type of the dataset will change after use of the Edit Metadata component. Use the Edit Metadata component to change metadata that's associated with columns in a dataset. This article describes a component included in Azure Machine Learning designer. ![]()
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