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MonkeyLearn

The MonkeyLearn modules allow you to create, update, and delete the classifiers, and extractors in your MonkeyLearn account.

Getting Started with MonkeyLearn

Prerequisites

  • A MonkeyLearn account

In order to use MonkeyLearn with Ibexa Connect, it is necessary to have a MonkeyLearn account. If you do not have one, you can create a MonkeyLearn account at app.monkeylearn.com/accounts/register.

Note

The module dialog fields that are displayed in bold (in the Ibexa Connect scenario, not in this documentation article) are mandatory!

Connecting MonkeyLearn to Ibexa Connect

To connect your MonkeyLearn account to Ibexa Connect you need to obtain the API Key from your MonkeyLearn account and insert it in the Create a connection dialog in the Ibexa Connect module.

1. Log in to your MonkeyLearn account.

2. Open the model you want to create or use and then click API. Copy the API Key to your clipboard.

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3. Go to Ibexa Connect and open the MonkeyLearn module's Create a connection dialog.

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4. In the Connection name field, enter the name of the connection.

5. In the API Key field, enter the API key copied in step 2 and click Continue.

The connection has been established.

Classifiers

List Classifiers

Returns all the available classifiers for the user.

Order by

Enter the order in which you want to list the classifiers.

For example, -created, ascending, or -updated, descending.

You can specify the order of the list. It can be ordered using any of the field names, either in ascending or descending order (adding ‘-’ before the name). Also, more than one criteria can be specified, separated by commas.

Limit

Enter the maximum number of classifiers Ibexa Connect must return during one scenario execution cycle.

Get a Classifiers

Returns information about a classifier including its settings, stats, and tags.
Model ID Select the Model ID whose details you want to retrieve.

Classify Text

Classifies the text with a given classifier.

Model ID

Select the Model ID whose text you want to classify.

Text

Enter the text you want to classify.

External ID

Enter any External ID which you want to include in the response.

Production Model

Select whether you want to perform the classification by the production model:

  • Yes

  • No

  • Not defined

Upload Classifier Data

Uploads data to a classifier.

Model ID

Select the Model ID whose classifier data you want to upload.

Data

Add the data objects:

Text

Enter the text to add or update.

Tags

Enter the list of keywords for referring to the text by their Numeric ID and their name.

Markers

Add the list of markers associated with the text.

Input Duplicate Strategy

Select the action to perform for duplicate texts in the request:

  • Merge

  • Keep First

  • Keep Last

Existing Duplicate Strategy

Select the action to perform for existing texts in the model:

  • Ignore

  • Overwrite

  • Merge

Create a Classifier

Creates a new classifier.

Name

Enter a name for the classifier model.

Description

Enter the details of the classifier model.

Algorithm

Select the algorithm in which the model is trained:

  • NB

  • SVM

Language

Select the language of the model.

Max Features

Enter the maximum number of features used when training the model.

The value must be greater than or equal to 10 and less than or equal to 10000.

Ngram Range

Enter a two-digit n-gram range used when training the model. For example, [2, 3].

The numbers must be between 1 and 3 and they indicate the minimum and maximum n for the n-grams used respectively.

Use Stemming

Select whether the stemming is used when training the model:

  • Yes

  • No

  • Not defined

Preprocess Numbers

Select whether the number preprocessing is done when training the model:

  • Yes

  • No

  • Not defined

Preprocess Names

Select whether the people names preprocessing is used when training the model:

  • Yes

  • No

  • Not defined

Preprocess Emails

Select whether the email addresses preprocessing is used when training the model:

  • Yes

  • No

  • Not defined

Preprocess URLs

Select whether the URLs preprocessing is used when training the model:

  • Yes

  • No

  • Not defined

Preprocess Social Media

Select whether the preprocessing of social media is done when training the model:

  • Yes

  • No

  • Not defined

Normalize Weights

Select whether the weights will be normalized when training the model:

  • Yes

  • No

  • Not defined

Stopwords

Enter the comma-separated list of the stopwords used when training the module.

Whitelist

Enter the comma-separated list of the whitelists of words used when training the module.

Tagging Strategy

Select the tagging strategy of the model:

  • Autodetect

  • Single

  • Multi

Update a Classifier

Updates a classifier name, description, and settings.

Model ID

Select the Model ID you want to update.

Name

Enter a name for the classifier model.

Description

Enter the details of the classifier model.

Algorithm

Select the algorithm in which the model is trained:

  • NB

  • SVM

Language

Select the language of the model.

Max Features

Enter the maximum number of features used when training the model.

The value must be greater than or equal to 10 and less than or equal to 10000.

Ngram Range

Enter a two-digit n-gram range used when training the model. For example, [2, 3].

The numbers must be between 1 and 3 and they indicate the minimum and maximum n for the n-grams used respectively.

Use Stemming

Select whether the stemming is used when training the model:

  • Yes

  • No

  • Not defined

Preprocess Numbers

Select whether the number preprocessing is done when training the model:

  • Yes

  • No

  • Not defined

Preprocess Names

Select whether the people names preprocessing is used when training the model:

  • Yes

  • No

  • Not defined

Preprocess Emails

Select whether the email addresses preprocessing is used when training the model:

  • Yes

  • No

  • Not defined

Preprocess URLs

Select whether the URLs preprocessing is used when training the model:

  • Yes

  • No

  • Not defined

Preprocess Social Media

Select whether the preprocessing of social media is done when training the model:

  • Yes

  • No

  • Not defined

Normalize Weights

Select whether the weights will be normalized when training the model:

  • Yes

  • No

  • Not defined

Stopwords

Enter the comma-separated list of the stopwords used when training the module.

Whitelist

Enter the comma-separated list of the whitelists of words used when training the module.

Tagging Strategy

Select the tagging strategy of the model:

  • Autodetect

  • Single

  • Multi

Delete a Classifier

Deletes a classifier.
Model ID Select the Model ID you want to delete.

Extractors

List Extractors

Returns all the available extractors for the user.

Order by

Enter the order in which you want to list the extractors.

For example, -created, ascending, or -updated, descending.

You can specify the order of the list. It can be ordered using any of the field names, either in ascending or descending order (adding ‘-’ before the name). Also, more than one criteria can be specified, separated by commas.

Limit

Enter the maximum number of extractors Ibexa Connect must return during one scenario execution cycle.

Get an Extractor

Returns information about an extractor.
Model ID Select the Model ID whose details you want to retrieve.

Extract Text

Extracts information from the text with a given extractor.

Model ID

Enter the maximum number of classifiers Ibexa Connect must return during one scenario execution cycle.

Text

Enter the text you want to extract.

External ID

Enter the External ID which you want to give in the request for the text to include in the response.

Production Model

Select whether you want to perform the classification by the production model:

  • Yes

  • No

  • Not defined

Other

Make an API Call

Performs an arbitrary authorized API call.
URL Enter a path relative to https://api.monkeylearn.com/. For example: /v3/classifiers

Note: For the list of available endpoints, refer to the MonkeyLearn API Documentation.

Method

Select the HTTP method you want to use:

GET to retrieve information for an entry.

POST to create a new entry.

PUT to update/replace an existing entry.

PATCH to make a partial entry update.

DELETE to delete an entry.

Headers

Enter the desired request headers. You don't have to add authorization headers; we already did that for you.

Query String

Enter the request query string.

Body

Enter the body content for your API call.

Example of Use - List Classifiers

The following API call returns all the classifiers from your MonkeyLearn account:

URL: /v3/classifiers

Method: GET

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Matches of the search can be found in the module's Output under Bundle > Body. In our example, 20 classifiers were returned:

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Method: GET

61d6a9d7235fd.png

Matches of the search can be found in the module's Output under Bundle > Body. In our example, 20 classifiers were returned:

61d6a9d85b093.png