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The code makes edit to the `measure_text_extraction_accuracy` function to allows dir of txt as well as json. The function also takes input `output_type` to be either "json" or "txt" only, and checks if the files under given directory/list contains only specified file type or not. To test this feature, run the following code: ```PYTHONPATH=. python unstructured/ingest/evaluate.py measure-text-extraction-accuracy-command --output_dir <clean-text-path> --source_dir <cct-label-path> --output_type txt```
25 lines
1.6 KiB
Plaintext
25 lines
1.6 KiB
Plaintext
Bank Good Credit
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Accredited with IABAC™
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( International Association of Business Analytics Certifications)`
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© DataMites™. All Rights Reserved | www.datamites.com
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Objective & Background
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Classify credit card customers as good / bad, based on information from internal and external sources.
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Data provided
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Demographic: Base file of with credit card history details. Only one record for every customer.
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Account: Contians data for various loans availed by the customer. Not related to credit card. Multiple records for every customer.
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Enquiries: Enquired made by customers for different loan purposes. Multiple records for every customer.
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© DataMites™. All Rights Reserved | www.datamites.com
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Design
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Data to be downloaded using SQL queries.
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Required information to be extracted from Account and Enquiry files and converted to one-to-one files.
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The columns from the two files should be merged with Demographic file using Left Join with “customer no” as key column, to create a final file. The final file should contain all the records in demographic and additional columns/features from Account and Enquiry files will get added to Demographic file.
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There will be many customers in account and enquiry file who will get left out. This is fine as we anyway don’t know their good/bad label for training purpose.
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© DataMites™. All Rights Reserved | www.datamites.com
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Analysis of Data
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Show using Excel File
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© DataMites™. All Rights Reserved | www.datamites.com
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Explain Coding / outcomes
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Show using Jupyter
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© DataMites™. All Rights Reserved | www.datamites.com
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Thank You
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© DataMites™. All Rights Reserved | www.datamites.com |