sim_SNN

Builds a shared nearest neighbors matrix and,
for each row (observation), returns the indices of the top neighbors
with the largest SNN overlap counts

A collection of large language model (LLM) text analysis methods
designed with psychological data in mind. Currently, LLMing (aka "lemming")
includes a text anomaly detection method based on the angle-based subspace
approach described by Zhang, Lin, and Karim (2015) and a text generation method.
<doi:10.1016/j.ress.2015.05.025>.

Lindley Slipetz

LLMing

Large Language Model (LLM) Tools for Psychological Text Analysis

Teague Henry

Siqi Sun

sim_SNN function

<dl><dt>z_dat</dt>
<dd>A dataframe with numeric columns</dd>
<dt>k</dt>
<dd>An integer representing number of nearest neighbors</dd>
<dt>tops</dt>
<dd>An integer representing how many of shared nearest neighbors to return</dd></dl>

Arguments

Compute shared nearest neighbors — sim_SNN

<dl>

<dt>z_dat</dt>
<dd>A dataframe with numeric columns</dd>


<dt>k</dt>
<dd>An integer representing number of nearest neighbors</dd>


<dt>tops</dt>
<dd>An integer representing how many of shared nearest neighbors to return</dd>

</dl>

sim_SNN: Compute shared nearest neighbors

Description

Usage

Value

Arguments