Dataiku

OCTOBER 20, 2021

Imagine that you’re just about to buy a new shirt at your local big box retailer. “Do Do you have an account with us?” asks the cashier. You think you may have signed up before, but can’t really remember.

105

105

AWS Big Data

JUNE 26, 2023

This has led to so-called fuzzy deduplication techniques to address the problem. Overview of solution In this post, we go through the various steps to apply ML-based fuzzy matching to harmonize customer data across two different datasets for auto and property insurance. Under Data classification tools, choose Record Matching.

Insurance 76

Insurance Visualization Data Lake Metrics 76

Ontotext

JULY 11, 2019

The similarity indices are a fuzzy match heuristic based on statistical semantics, which is particularly useful when retrieving the closest related texts or when grouping a cluster of graph nodes based on their topology. The plugin integrates the Semantic vectors library and its underlying Random Indexing algorithm.

Statistics 40

Statistics Modeling Metadata IT 40

Ontotext

JULY 11, 2019

The similarity indices are a fuzzy match heuristic based on statistical semantics, which is particularly useful when retrieving the closest related texts or when grouping a cluster of graph nodes based on their topology. The plugin integrates the Semantic vectors library and its underlying Random Indexing algorithm.

Statistics 40

Statistics Modeling Metadata Enterprise 40

AWS Big Data

FEBRUARY 8, 2023

We import an open-source fuzzy matching Python library to Amazon Redshift, create a simple fuzzy matching user-defined function (UDF), and then create a procedure that weights multiple columns in a table to find matches based on user input. Choose the closest matched URID, but only if there is a >90% match.

Data Quality 73

Data Quality Testing Data Warehouse Unstructured Data 73

Domino Data Lab

JUNE 8, 2021

and we need to rewrite (9) to match the above format. In this article we went over the mathematics of the Support Vector Machine and its associated learning algorithm. Spatial-taxon information granules as used in iterative fuzzy-decision-making for image segmentation. end{aligned} end{equation} $$. References. Barghout, L.

Optimization 76

Optimization Machine Learning Measurement Data Science 76

Edwin Chen

JULY 17, 2011

Note that this reconstruction may not match the original preferences.) So by adding (Positive(e_{ij}) - Negative(e_{ij})) to each edge weight, we’re helping the network’s daydreams better match the reality of our training examples. This can speed up the learning by taking advantage of fast matrix-multiplication algorithms.

Measurement 75

Measurement Modeling IT 75