Text Classifiers

Create text analysis models that can assign tags or categories to text based on content.

What it does: Understand what a given text is about based on custom criteria.

Text Example

“I ordered a Nintendo and Donkey Kong from your store last week. I’m furious to find out that the tracking number doesn’t work and my order might be lost. Please respond ASAP.”

Automatically Tagged As:
Order Issue

What it does: Determine whether a text is positive, negative, or neutral

Text Example

“My experience so far with the product has been fantastic. The interface is really fast and the customer service is excellent. I’m going to be thinking about upgrading soon.”

Automatically Tagged As:
Positive

What it does: Detect the intentions behind text responses

Text Example

“Hi Jack, thanks for the email, your platform looks promising. Can we schedule a call tomorrow to see a demo? Please let me know when you are available. Thanks, Koko.”

Automatically Tagged As:
Interested in Demo

How to Build Custom Classifiers

Easily build and train a machine learning model to tag and classify your text.

1. Upload Data to MonkeyLearn

Create a model and import your text data by uploading files directly or by connecting with third-party apps.

2. Define Tags

Define the tags you will use for the classifier. These tags will be used to classify or categorize text by your criteria.

3. Tag & Train

Train the classifier by selecting the appropriate tag for each text that appears. The classifier will begin to learn right before your eyes.

4. Evaluate & Improve

Test your trained model to see predicted tags. Improve the classifier by tagging more data or working in your model metrics.

5. Put Your Classifier to Work

Use your new classifier to analyze new or historical texts. Either upload a file to process text in a batch, use integrations with third-party apps, or our API to classify text automatically.