semvec/pypi-packages huggingface dataset:
predecon-exioreed 0.1.1
PreDeCon - An Implementation in Python, Compatible With Scikit-Learn
Requires Python: >=3.6

# PreDeCon

This repository is not associated with the original authors of [Boehm,2004].

## About

_Subspace Preference Weighted Density Connected Clustering_ (PreDeCon) [Boehm,2004] can be seen as a
modification to the famous DBSCAN [Ester,1996] that addresses problems which arise in
high-dimensional spaces.

## Installation

Install with `pip`.

From PyPI

```
$ pip install predecon-exioreed
```

Alternatively, from source

```
$ pip install git+https://github.com/exioReed/PreDeCon@master#egg=PreDeCon-exioreed
```

or

```
$ git clone https://github.com/exioReed/PreDeCon.git
$ cd PreDeCon
$ pip install .
```

## References

`[Boehm,2004]` Boehm, C. et al., "Density Connected Clustering with Local Subspace Preferences".
In: _Proceedings of the 4th IEEE Internation Conference on Data Mining (ICDM)_,
Brighton, UK, 2004.

`[Ester,1996]` Ester, M. et al., "A Density-Based Algorithm for Discovering Clusters in Large
Spatial Databases with Noise".
In: _Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining_,
Portland, OR, 1996.
scicat 1.1.23
a scicat search package

# Scicat Search

[![Build Status](https://travis-ci.org/garethcmurphy/scicat_pkg.svg?branch=master)](https://travis-ci.org/garethcmurphy/scicat_pkg)
[![Coverage Status](https://coveralls.io/repos/github/garethcmurphy/scicat_pkg/badge.svg?branch=master)](https://coveralls.io/github/garethcmurphy/scicat_pkg?branch=master)

This package queries data at scicat.esss.se.
You can search using a simple text search or by passing a python dictionary containing fields to query.