{"action":"created","issue":{"url":"https://api.github.com/repos/marcotcr/lime/issues/263","repository_url":"https://api.github.com/repos/marcotcr/lime","labels_url":"https://api.github.com/repos/marcotcr/lime/issues/263/labels{/name}","comments_url":"https://api.github.com/repos/marcotcr/lime/issues/263/comments","events_url":"https://api.github.com/repos/marcotcr/lime/issues/263/events","html_url":"https://github.com/marcotcr/lime/issues/263","id":387679512,"node_id":"MDU6SXNzdWUzODc2Nzk1MTI=","number":263,"title":"Support for Sequence Models","user":{"login":"rhlewd","id":7934170,"node_id":"MDQ6VXNlcjc5MzQxNzA=","avatar_url":"https://avatars1.githubusercontent.com/u/7934170?v=4","gravatar_id":"","url":"https://api.github.com/users/rhlewd","html_url":"https://github.com/rhlewd","followers_url":"https://api.github.com/users/rhlewd/followers","following_url":"https://api.github.com/users/rhlewd/following{/other_user}","gists_url":"https://api.github.com/users/rhlewd/gists{/gist_id}","starred_url":"https://api.github.com/users/rhlewd/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/rhlewd/subscriptions","organizations_url":"https://api.github.com/users/rhlewd/orgs","repos_url":"https://api.github.com/users/rhlewd/repos","events_url":"https://api.github.com/users/rhlewd/events{/privacy}","received_events_url":"https://api.github.com/users/rhlewd/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2018-12-05T10:02:29Z","updated_at":"2018-12-07T00:04:17Z","closed_at":"2018-12-07T00:04:17Z","author_association":"NONE","body":"Hello,\r\nI have been working on sequence models for classifying multivariate(for e.g. 5 variables) time series data into 2 classes. \r\nI want to use LIME to explain the contribution of a particular variable to a predicted score. Is this possible with LIME? \r\nI saw lot of examples on internet but none of them seem to address this particular model type, hence posting it here. "},"comment":{"url":"https://api.github.com/repos/marcotcr/lime/issues/comments/445075374","html_url":"https://github.com/marcotcr/lime/issues/263#issuecomment-445075374","issue_url":"https://api.github.com/repos/marcotcr/lime/issues/263","id":445075374,"node_id":"MDEyOklzc3VlQ29tbWVudDQ0NTA3NTM3NA==","user":{"login":"marcotcr","id":698010,"node_id":"MDQ6VXNlcjY5ODAxMA==","avatar_url":"https://avatars3.githubusercontent.com/u/698010?v=4","gravatar_id":"","url":"https://api.github.com/users/marcotcr","html_url":"https://github.com/marcotcr","followers_url":"https://api.github.com/users/marcotcr/followers","following_url":"https://api.github.com/users/marcotcr/following{/other_user}","gists_url":"https://api.github.com/users/marcotcr/gists{/gist_id}","starred_url":"https://api.github.com/users/marcotcr/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/marcotcr/subscriptions","organizations_url":"https://api.github.com/users/marcotcr/orgs","repos_url":"https://api.github.com/users/marcotcr/repos","events_url":"https://api.github.com/users/marcotcr/events{/privacy}","received_events_url":"https://api.github.com/users/marcotcr/received_events","type":"User","site_admin":false},"created_at":"2018-12-07T00:04:17Z","updated_at":"2018-12-07T00:04:17Z","author_association":"OWNER","body":"You can flatten the time series and use `LimeTabularExplainer`. Take a look at [this](https://github.com/marcotcr/lime/blob/master/lime/lime_tabular.py#L446) wrapper for an example."}}
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