![]() In this case, the review comment column ("col0") is the Feature column. All of the columns in the dataset besides the Label are automatically selected as Features. The columns that are used to help predict the Label are called Features. The Label is what you're predicting, which in this case is the sentiment found in the second column ("col1") of the dataset. Under Column to predict (Label), select "col1". Since your dataset does not have a header, headers are auto-generated ("col0" and "col1"). Once you select your dataset, a preview of your data appears in the Data Preview section. Select File as the input data source type.īrowse for yelp_labelled.txt. In this case, you'll add yelp_labelled.txt from a file. ![]() In Model Builder, you can add data from a local file or connect to a SQL Server database. Model Builder will guide you through the process of building a machine learning model in the following steps. The mbconfig file is simply a JSON file that keeps track of the state of the UI.
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