-
Notifications
You must be signed in to change notification settings - Fork 1
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
1 parent
10cab77
commit cded508
Showing
6 changed files
with
103 additions
and
63 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,89 @@ | ||
| // ============================================================== | ||
| // Find all successfully executed experiments for specific model | ||
| // ============================================================== | ||
| db.exp_nulls_data_cleaning.aggregate([ | ||
| { | ||
| $match: { | ||
| model_name: 'gandalf_clf', | ||
| tag: 'OK' | ||
| } | ||
| }, | ||
| { | ||
| $group: { | ||
| _id: { | ||
| dataset_name: "$dataset_name", | ||
| null_imputer_name: "$null_imputer_name", | ||
| evaluation_scenario: "$evaluation_scenario", | ||
| model_name: "$model_name", | ||
| experiment_iteration: "$experiment_iteration" | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| $sort: { | ||
| "_id.dataset_name": 1, | ||
| "_id.null_imputer_name": 1, | ||
| "_id.evaluation_scenario": 1, | ||
| "_id.experiment_iteration": 1 | ||
| } | ||
| }, | ||
| { | ||
| $project: { | ||
| _id: 0, | ||
| dataset_name: "$_id.dataset_name", | ||
| null_imputer_name: "$_id.null_imputer_name", | ||
| evaluation_scenario: "$_id.evaluation_scenario", | ||
| model_name: "$_id.model_name", | ||
| experiment_iteration: "$_id.experiment_iteration" | ||
| } | ||
| } | ||
| ]); | ||
|
|
||
|
|
||
| // ========================================================================================================== | ||
| // Find best models based on F1 for specific dataset and each experiment iteration. | ||
| // If model results are the same, two models will be displayed per one experiment iteration as the best ones. | ||
| // ========================================================================================================== | ||
| db.exp_nulls_data_cleaning.aggregate([ | ||
| { | ||
| $match: { dataset_name: "law_school", evaluation_scenario: "baseline", model_name: {$ne: "tabpfn_clf"}, metric: "F1", subgroup: "overall", tag: "OK" } | ||
| }, | ||
| { | ||
| $group: { | ||
| _id: "$experiment_iteration", // Group by 'group' | ||
| maxTotalValue: { $max: "$metric_value" } // Find the maximum total_value for each group | ||
| } | ||
| }, | ||
| { | ||
| $lookup: { // Use $lookup to join original documents back to max values | ||
| from: "exp_nulls_data_cleaning", // Perform a self-join | ||
| let: { groupId: "$_id", maxValue: "$maxTotalValue" }, | ||
| pipeline: [ | ||
| { $match: { | ||
| $expr: { | ||
| $and: [ | ||
| { $eq: ["$experiment_iteration", "$$groupId"] }, // Match group | ||
| { $eq: ["$metric_value", "$$maxValue"] }, // Match max value | ||
| { $eq: ["$dataset_name", "law_school"] }, | ||
| { $eq: ["$evaluation_scenario", "baseline"] }, | ||
| { $eq: ["$metric", "F1"] }, | ||
| { $eq: ["$subgroup", "overall"] }, | ||
| { $eq: ["$tag", "OK"] }, | ||
| { $ne: ["$model_name", "tabpfn_clf"] } | ||
| ] | ||
| } | ||
| }} | ||
| ], | ||
| as: "maxValueDocs" | ||
| } | ||
| }, | ||
| { | ||
| $unwind: "$maxValueDocs" // Unwind the array to return documents | ||
| }, | ||
| { | ||
| $replaceRoot: { newRoot: "$maxValueDocs" } // Replace root to return original documents | ||
| }, | ||
| { | ||
| $project: { _id: 0, dataset_split_seed: 0, exp_pipeline_guid: 0, model_params: 0, model_init_seed: 0, null_imputer_name: 0 } // Optionally, hide the total_value field from output | ||
| } | ||
| ]); |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,6 +1,5 @@ | ||
| dataset_name: diabetes | ||
| bootstrap_fraction: 0.8 | ||
| n_estimators: 5 | ||
| #n_estimators: 50 | ||
| n_estimators: 50 | ||
| computation_mode: error_analysis | ||
| sensitive_attributes_dct: {'Gender': 'Female'} |