euclidean_curve

Plot S-Curve for a LSH with given hyperparameters

Empowers users to fuzzily-merge data frames with millions or tens of millions of rows in minutes with low memory usage. The package uses the locality sensitive hashing algorithms developed by Datar, Immorlica, Indyk and Mirrokni (2004) <doi:10.1145/997817.997857>, and Broder (1998) <doi:10.1109/SEQUEN.1997.666900> to avoid having to compare every pair of records in each dataset, resulting in fuzzy-merges that finish in linear time.

Beniamino Green

zoomerjoin

Superlatively Fast Fuzzy Joins

Etienne Bacher

The authors of the dependency Rust crates 

euclidean_curve function

<dl><dt>n_bands</dt>
<dd>The number of LSH bands calculated</dd>
<dt>band_width</dt>
<dd>The number of hashes in each band</dd>
<dt>r</dt>
<dd>the "r" hyperparameter used to govern the sensitivity of the hash.</dd>
<dt>up_to</dt>
<dd>the right extent of the x axis.</dd></dl>

Arguments

Plot S-Curve for a LSH with given hyperparameters — euclidean_curve

<dl>

<dt>n_bands</dt>
<dd>The number of LSH bands calculated</dd>


<dt>band_width</dt>
<dd>The number of hashes in each band</dd>


<dt>r</dt>
<dd>the "r" hyperparameter used to govern the sensitivity of the hash.</dd>


<dt>up_to</dt>
<dd>the right extent of the x axis.</dd>

</dl>

euclidean_curve: Plot S-Curve for a LSH with given hyperparameters

Description

Usage

Value

Arguments