StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics https://doi.org/10.1109/TVCG.2020.3030352
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StackGenVis/frontend/node_modules/strongly-connected-components/README.md

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strongly-connected-components
=============================
Given a directed graph, splits it into [strongly connected components](http://en.wikipedia.org/wiki/Strongly_connected_component).
## Example
```javascript
var scc = require("strongly-connected-components")
var adjacencyList = [
[4], // 0
[0,2], // 1
[1,3], // 2
[2], // 3
[1], // 4
[4,6], // 5
[5,2], // 6
[7,6,3], // 7
]
console.log(scc(adjacencyList))
```
## Install
npm install strongly-connected-components
## API
### `require("strongly-connected-components")(adjacencyList)`
Computes the strongly connected components of a graph using Tarjan's algorithm.
* `adjacencyList` is an array of lists representing the directed edges of the graph
**Returns** An object containing:
* `components`: an array of arrays representing the partitioning of the vertices in the graph into connected components.
* `adjacencyList`: an array lists representing the directed edges of the directed acyclic graph between the strongly connected components
## Credits
(c) 2013 Mikola Lysenko. MIT License. Based on the [implementation of Tarjan's algorithm on Wikipedia.](http://en.wikipedia.org/wiki/Tarjan's_strongly_connected_components_algorithm)