{"action":"created","comment":{"url":"https://api.github.com/repos/h2oai/h2o-3/pulls/comments/232814971","pull_request_review_id":174097232,"id":232814971,"node_id":"MDI0OlB1bGxSZXF1ZXN0UmV2aWV3Q29tbWVudDIzMjgxNDk3MQ==","diff_hunk":"@@ -1223,41 +1224,59 @@ else if (isWeights && computeMetrics) {\n     if( good == names.length || (response != null && test.find(response) == -1 && good == names.length - 1) )  // Only update if got something for all columns\n       test.restructure(names,vvecs,good);\n \n-    boolean haveCategoricalPredictors = false;\n     if (expensive && checkCategoricals && !catEncoded) {\n-      for (int i=0; i<test.numCols(); ++i) {\n-        if (test.names()[i].equals(response)) continue;\n-        if (test.names()[i].equals(weights)) continue;\n-        if (test.names()[i].equals(offset)) continue;\n-        if (test.names()[i].equals(fold)) continue;\n-        // either the column of the test set is categorical (could be a numeric col that's already turned into a factor)\n-        if (test.vec(i).cardinality() > 0) {\n-          haveCategoricalPredictors = true;\n-          break;\n-        }\n-        // or a equally named column of the training set is categorical, but the test column isn't (e.g., numeric column provided to be converted to a factor)\n-        int whichCol = ArrayUtils.find(names, test.name(i));\n-        if (whichCol >= 0 && domains[whichCol] != null) {\n-          haveCategoricalPredictors = true;\n-          break;\n-        }\n+      final boolean hasCategoricalPredictors = hasCategoricalPredictors(test, response, weights, offset, fold, names, domains);\n+\n+      // check if we first need to expand categoricals before calling this method again\n+      if (hasCategoricalPredictors) {","path":"h2o-core/src/main/java/hex/Model.java","position":65,"original_position":65,"commit_id":"4195453da13a844cd952f9a4023813f2f840326c","original_commit_id":"4195453da13a844cd952f9a4023813f2f840326c","user":{"login":"michalkurka","id":20690218,"node_id":"MDQ6VXNlcjIwNjkwMjE4","avatar_url":"https://avatars2.githubusercontent.com/u/20690218?v=4","gravatar_id":"","url":"https://api.github.com/users/michalkurka","html_url":"https://github.com/michalkurka","followers_url":"https://api.github.com/users/michalkurka/followers","following_url":"https://api.github.com/users/michalkurka/following{/other_user}","gists_url":"https://api.github.com/users/michalkurka/gists{/gist_id}","starred_url":"https://api.github.com/users/michalkurka/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/michalkurka/subscriptions","organizations_url":"https://api.github.com/users/michalkurka/orgs","repos_url":"https://api.github.com/users/michalkurka/repos","events_url":"https://api.github.com/users/michalkurka/events{/privacy}","received_events_url":"https://api.github.com/users/michalkurka/received_events","type":"User","site_admin":false},"body":"I see! Sorry @Pscheidl! my mistake ","created_at":"2018-11-12T21:18:23Z","updated_at":"2018-11-12T21:18:23Z","html_url":"https://github.com/h2oai/h2o-3/pull/3023#discussion_r232814971","pull_request_url":"https://api.github.com/repos/h2oai/h2o-3/pulls/3023","author_association":"CONTRIBUTOR","_links":{"self":{"href":"https://api.github.com/repos/h2oai/h2o-3/pulls/comments/232814971"},"html":{"href":"https://github.com/h2oai/h2o-3/pull/3023#discussion_r232814971"},"pull_request":{"href":"https://api.github.com/repos/h2oai/h2o-3/pulls/3023"}},"in_reply_to_id":232799680},"pull_request":{"url":"https://api.github.com/repos/h2oai/h2o-3/pulls/3023","id":229391894,"node_id":"MDExOlB1bGxSZXF1ZXN0MjI5MzkxODk0","html_url":"https://github.com/h2oai/h2o-3/pull/3023","diff_url":"https://github.com/h2oai/h2o-3/pull/3023.diff","patch_url":"https://github.com/h2oai/h2o-3/pull/3023.patch","issue_url":"https://api.github.com/repos/h2oai/h2o-3/issues/3023","number":3023,"state":"open","locked":false,"title":"PUBDEV-5352 - Cannot use checkpoint on new data in DRF. Added enhance…","user":{"login":"Pscheidl","id":8769110,"node_id":"MDQ6VXNlcjg3NjkxMTA=","avatar_url":"https://avatars3.githubusercontent.com/u/8769110?v=4","gravatar_id":"","url":"https://api.github.com/users/Pscheidl","html_url":"https://github.com/Pscheidl","followers_url":"https://api.github.com/users/Pscheidl/followers","following_url":"https://api.github.com/users/Pscheidl/following{/other_user}","gists_url":"https://api.github.com/users/Pscheidl/gists{/gist_id}","starred_url":"https://api.github.com/users/Pscheidl/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Pscheidl/subscriptions","organizations_url":"https://api.github.com/users/Pscheidl/orgs","repos_url":"https://api.github.com/users/Pscheidl/repos","events_url":"https://api.github.com/users/Pscheidl/events{/privacy}","received_events_url":"https://api.github.com/users/Pscheidl/received_events","type":"User","site_admin":false},"body":"…ment to Python checkpoint setter.\r\n\r\nhttps://0xdata.atlassian.net/browse/PUBDEV-5352\r\n\r\nProblem is column skipping. The method `protected void ignoreBadColumns(int npredictors, boolean expensive){ ... }`\r\n\r\nignores column names present in checkpointed model and just deletes/skips those 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