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 {{product name}} , 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 https //app monkeylearn com/accounts/register/ connecting monkeylearn to {{product name}} to connect your monkeylearn account to {{product name}} you need to obtain the api key from your monkeylearn account and insert it in the create a connection dialog in the {{product name}} 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 {{product name}} 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 user connection monkeylearn docid\ o4i84sfi7wdr4hfpsyps1 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 {{product name}} must return during one {{scenario singular lowercase}} execution cycle get a classifiers returns information about a classifier including its settings, stats, and tags connection monkeylearn docid\ o4i84sfi7wdr4hfpsyps1 model id select the model id whose details you want to retrieve classify text classifies the text with a given classifier connection monkeylearn docid\ o4i84sfi7wdr4hfpsyps1 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 monkeylearn docid\ o4i84sfi7wdr4hfpsyps1 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 monkeylearn docid\ o4i84sfi7wdr4hfpsyps1 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 monkeylearn docid\ o4i84sfi7wdr4hfpsyps1 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 monkeylearn docid\ o4i84sfi7wdr4hfpsyps1 model id select the model id you want to delete extractors list extractors returns all the available extractors for the user connection monkeylearn docid\ o4i84sfi7wdr4hfpsyps1 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 {{product name}} must return during one {{scenario singular lowercase}} execution cycle get an extractor returns information about an extractor connection monkeylearn docid\ o4i84sfi7wdr4hfpsyps1 model id select the model id whose details you want to retrieve extract text extracts information from the text with a given extractor connection monkeylearn docid\ o4i84sfi7wdr4hfpsyps1 model id enter the maximum number of classifiers {{product name}} must return during one {{scenario singular lowercase}} 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 monkeylearn docid\ o4i84sfi7wdr4hfpsyps1 url enter a path relative to https //api monkeylearn com/ for example /v3/classifiers 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 for the list of available endpoints, refer to the monkeylearn api documentation https //monkeylearn com/api 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 bundle > body in our example, 20 classifiers were returned