{"action":"created","comment":{"url":"https://api.github.com/repos/Benjamin-Lee/deep-rules/pulls/comments/264248858","pull_request_review_id":212856010,"id":264248858,"node_id":"MDI0OlB1bGxSZXF1ZXN0UmV2aWV3Q29tbWVudDI2NDI0ODg1OA==","diff_hunk":"@@ -1,14 +1,14 @@\n ## Tip 2: Use traditional methods to establish performance baselines {#baselines}\n \n-Before diving into a fancy thousand-layer neural network, always implement at least a simple model to establish an adequate performance baseline.\n-For example, researchers can build multinomial logistic regression or random forest models using the same software framework that is being used for DL and evaluate its classification performance.\n+It is important to implement a simple model to establish an adequate performance baseline, since it is easy to fall into the trap of an unnecessarily convoluted analysis.\n+For example, a researcher could first a build a multinomial logistic regression or random forest model using the same software framework planned for DL to first evaluate the classification performance.","path":"content/04.baselines.md","position":6,"original_position":6,"commit_id":"7072e319ef918d4fd9827921b624ac5a70f2e3b3","original_commit_id":"7072e319ef918d4fd9827921b624ac5a70f2e3b3","user":{"login":"agitter","id":3532898,"node_id":"MDQ6VXNlcjM1MzI4OTg=","avatar_url":"https://avatars0.githubusercontent.com/u/3532898?v=4","gravatar_id":"","url":"https://api.github.com/users/agitter","html_url":"https://github.com/agitter","followers_url":"https://api.github.com/users/agitter/followers","following_url":"https://api.github.com/users/agitter/following{/other_user}","gists_url":"https://api.github.com/users/agitter/gists{/gist_id}","starred_url":"https://api.github.com/users/agitter/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/agitter/subscriptions","organizations_url":"https://api.github.com/users/agitter/orgs","repos_url":"https://api.github.com/users/agitter/repos","events_url":"https://api.github.com/users/agitter/events{/privacy}","received_events_url":"https://api.github.com/users/agitter/received_events","type":"User","site_admin":false},"body":"This isn't your edit, but do popular DL frameworks support random forest?  That recommendation seemed out of place to me in the initial draft.  Logistic regression makes sense.","created_at":"2019-03-11T14:09:47Z","updated_at":"2019-03-11T14:09:47Z","html_url":"https://github.com/Benjamin-Lee/deep-rules/pull/162#discussion_r264248858","pull_request_url":"https://api.github.com/repos/Benjamin-Lee/deep-rules/pulls/162","author_association":"COLLABORATOR","_links":{"self":{"href":"https://api.github.com/repos/Benjamin-Lee/deep-rules/pulls/comments/264248858"},"html":{"href":"https://github.com/Benjamin-Lee/deep-rules/pull/162#discussion_r264248858"},"pull_request":{"href":"https://api.github.com/repos/Benjamin-Lee/deep-rules/pulls/162"}}},"pull_request":{"url":"https://api.github.com/repos/Benjamin-Lee/deep-rules/pulls/162","id":259966970,"node_id":"MDExOlB1bGxSZXF1ZXN0MjU5OTY2OTcw","html_url":"https://github.com/Benjamin-Lee/deep-rules/pull/162","diff_url":"https://github.com/Benjamin-Lee/deep-rules/pull/162.diff","patch_url":"https://github.com/Benjamin-Lee/deep-rules/pull/162.patch","issue_url":"https://api.github.com/repos/Benjamin-Lee/deep-rules/issues/162","number":162,"state":"open","locked":false,"title":"Some tweaks to baselines/tip 2. 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