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Replace filterIncompleteRecords boolean with Imputation Enum for Enhanced Data Handling #23
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I will take this ticket, gather my thoughts on how I would solve this, and present my idea. |
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This commit introduces the 'handler' package under 'de.eudx.data' to handle the cleaning and processing of incomplete records within a dataset, in correspondence with issue Samyssmile#23. Changes Made: - Added 'handler' package under 'de.edux.data' - Introduced 'EIncompleteRecordsHandlerStratetgy' enum with the constans: DO_NOT_HANDLE, DROP_RECORDS, FILL_RECORDS_WITH_AVERAGE - Introduced 'IIncompleteRecordsHandler' interface - Implemented 'DropIncompleteRecordsHandler' class - Implemented 'AverageFillIncompleteRecordsHandler' class - Implemented 'DoNotHandleIncompleteRecords' class because of DataProcessorTest.testLoadDataWithoutNormalizationAndShuffling() - Started to write the tests for the above mentioned classes and their methods - Revired the existing codebase to be compatible with the new enum
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This commit introduces the 'handler' package under 'de.eudx.data' to handle the cleaning and processing of incomplete records within a dataset, in correspondence with issue Samyssmile#23. Changes Made: - Added 'handler' package under 'de.edux.data' - Introduced 'EIncompleteRecordsHandlerStratetgy' enum with the constans: DO_NOT_HANDLE, DROP_RECORDS, FILL_RECORDS_WITH_AVERAGE - Introduced 'IIncompleteRecordsHandler' interface - Implemented 'DropIncompleteRecordsHandler' class - Implemented 'AverageFillIncompleteRecordsHandler' class - Implemented 'DoNotHandleIncompleteRecords' class because of DataProcessorTest.testLoadDataWithoutNormalizationAndShuffling() - Started to write the tests for the above mentioned classes and their methods - Revired the existing codebase to be compatible with the new enum
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Feat(#23) Replace filterIncompleteRecords boolean with Imputation Enum for Enhanced Data Handling
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There is an open discussion for this ticket. #62
In our data processing logic, we currently use a boolean named filterIncompleteRecords to decide whether to filter out incomplete records or not. To provide more flexibility and future extensibility in handling missing data, we propose replacing this boolean with an enum named Imputation.
Let see on this example tiger dataset.
With filterIncompleteRecords = true, our Data Processing Class will auto remove Amur Tiger from the dataset, because the size value is missed.
The new Imputation enum would have various strategies such as MEDIAN, MODE, FILTEROUT, and AVERAGE. For the scope of this ticket, we'll focus on implementing FILTEROUT and AVERAGE, MODE.
Advantages of this new Feature
A user can auto fill missed values.
Hint
How filterIncompleteRecords works you can see in the Seaborn Pinguin k-nearest neighbors algorithm (knn) example.
https://github.com/Samyssmile/edux/blob/main/example/src/main/java/de/example/knn/KnnSeabornExample.java
https://journalofbigdata.springeropen.com/articles/10.1186/s40537-021-00516-9
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