| Name | core-graph JSON |
| Version |
0.0.6
JSON |
| download |
| home_page | None |
| Summary | A utility package for data science |
| upload_time | 2024-08-19 08:36:14 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.11 |
| license | Copyright (c) 2024 Kevin Khang Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
api
google
aws
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Introduction
Data tools to increase productivity in your workflow
# How to setup
Install with pip:
```
pip install core_graph
```
# Metrics in community finding:
## 1. Modularity
Modularity measures the strength of division of a network into communities.
It compares the density of connections inside communities to the density of connections between communities.
Modularity values typically range from -1 to 1:
- Positive values indicate more edges within communities than would be expected by random chance.
- Negative values indicate fewer edges within communities than expected by random chance.
In practice, modularity values for real networks with good community structure often fall in the range of 0.3 to 0.7.
Using Modularity for Comparison:
- Higher modularity generally indicates a better community structure.
- You can compare the modularity scores of different community detection algorithms on the same network.
- The algorithm that produces the highest modularity score is often considered to have found the best community
structure.
## 2. Codelength
Codelength is a central concept in Infomap's approach to community detection.
It's based on the principle of data compression and information theory:
- Codelength represents the average number of bits needed to describe a random walk on the network.
- A lower codelength indicates a better partition of the network into communities.
- Infomap aims to minimize this codelength, which corresponds to finding the best community structure.
The codelength consists of two parts:
- The description length of movements between modules
- The description length of movements within modules
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