Data cleansing problem statement: Data in a record are often duplicated. How do we find the duplicate probability ?
We'll be using the UC Irvine Machine Learning Repo dataset. From the book (see the References section) :
The data set we’ll analyze was curated from a record linkage study per‐ formed at a German hospital in 2010, and it contains several million pairs of patient records that were matched according to several different criteria, such as the patient’s name (first and last), address, and birthday. Each matching field was assigned a numerical score from 0.0 to 1.0 based on how similar the strings were, and the data was then hand-labeled to identify which pairs represented the same person and which did not. The underlying values of the fields that were used to create the data set were removed to protect the privacy of the patients. Numerical identifiers, the match scores for the fields, and the label for each pair (match versus nonmatch) were pub‐ lished for use in record linkage research.
This data set is available at this URL : https://bit.ly/1Aoywaq
To download it, run this command : $ curl -L -o data.zip https://bit.ly/1Aoywaq
$ git clone https://github.com/redouane-dev/spark-record-deduplicating.git$ cd spark-record-deduplicating$ ./gradlew build
$ mkdir -p data/linkage$ curl -L -o data/data.zip https://bit.ly/1Aoywaq$ unzip -d ./data ./data/data.zip$ unzip -d ./data/linkage './data/block_*.zip'$ rm -v ./data/block_*.zip(Optionaly remove the .zip files)
$ ./gradlew run
- Find how to plot the ROC (Receiver Operating Characteristic) in Scala
- Try new sets of features (consider low-value or deprecated features for the scoring function)
- "Advanced Analytics with Spark by Sandy Ryza, Uri Laserson, Sean Owen, and Josh Wills (O’Reilly). Copyright 2015 Sandy Ryza, Uri Laserson, Sean Owen, and Josh Wills, 978-1-491-91276-8."