Table of Contents

MonkeyLearn

Active with remarks
This application needs additional settings. Please follow the documentation below to create your own connectionUnique, active service acces point to a network. There are different types of connections (API key, Oauth…). More.

MonkeyLearn

The MonkeyLearn modulesThe module is an application or tool within the Boost.space system. The entire system is built on this concept of modularity. (module - Contacts) More 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 Boost.spaceCentralization and synchronization platform, where you can organize and manage your data. More IntegratorPart of the Boost.space system, where you can create your connections and automate your processes. More, 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 moduleThe module is an application or tool within the Boost.space system. The entire system is built on this concept of modularity. (module - Contacts) More dialog fields that are displayed in bold (in the Boost.space Integrator scenarioA specific connection between applications in which data can be transferred. Two types of scenarios: active/inactive. More, not in this documentation article) are mandatory!

Connecting MonkeyLearn to Boost.space Integrator

To connect your MonkeyLearn account to Boost.space Integrator you need to obtain the API Key from your MonkeyLearn account and insert it in the Create a connection dialog in the Boost.space Integrator 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.

3. Go to Boost.space Integrator and open the MonkeyLearn module’s Create a connection dialog.

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 userCan use the system on a limited basis based on the rights assigned by the admin. More.

Connection

Establish a connection to your MonkeyLearn account.

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 Boost.space Integrator must return during one scenario execution cycleA cycle is the operation and commit/rollback phases of scenario execution. A scenario may have one or more cycles (one is the default)..

Get a Classifiers

Returns information about a classifier including its settings, stats, and tags.

Connection	Establish a connection to your MonkeyLearn account.
Model ID	Select the Model ID whose details you want to retrieve.

Classify Text

Classifies the text with a given classifier.

Connection	Establish a connection to your MonkeyLearn account.
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.

Connection	Establish a connection to your MonkeyLearn account.
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.

Connection	Establish a connection to your MonkeyLearn account.
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.

Connection	Establish a connection to your MonkeyLearn account.
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.

Connection	Establish a connection to your MonkeyLearn account.
Model ID	Select the Model ID you want to delete.

Extractors

List Extractors

Returns all the available extractors for the user.

Connection

Establish a connection to your MonkeyLearn account.

Order by

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

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

Limit

Enter the maximum number of extractors Boost.space Integrator must return during one scenario execution cycle.

Get an Extractor

Returns information about an extractor.

Connection	Establish a connection to your MonkeyLearn account.
Model ID	Select the Model ID whose details you want to retrieve.

Extract Text

Extracts information from the text with a given extractor.

Connection	Establish a connection to your MonkeyLearn account.
Model ID	Enter the maximum number of classifiers Boost.space Integrator 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.

Connection

Establish a connection to your MonkeyLearn account.

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

Matches of the search can be found in the module’s Output under BundleA bundle is a chunk of data and the basic unit for use with modules. A bundle consists of items, similar to how a bag may contain separate, individual items. More > Body. In our example, 20 classifiers were returned: