Running and deploying a Naive Bayes classifier for text data using R and Docker. You can use this NLP classifier to understand natural language senten

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Running and deploying a Naive Bayes classifier for text data using R and Docker. You can use this NLP classifier to understand natural language sentences and assign a label to them. There is no built-in way in R to do this task, so we created a classifier for it ourselves.

Use an editor like RStudio and make sure that you set your working directory. Then run the following commands within R Studio to install the required packages:

How to build Use this command to build your docker container. Note that this can take several minutes up to an hour to build because some required packages may need to be installed from source.

Use this command to run the dockerfile in the background. Note that if you localhost 8000 port is already in use, you need to choose another port.

Your custom training data needs to have the same structure as the example data: One row with an index for each observation, one row named "text" which includes each observation of your text data and one row that contains the label you set for each observation.

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