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Merge pull request #40 from lauraguevara97/patch-1

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Update README.md
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Ilya Grigorik
2018-03-12 07:58:31 -07:00
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@@ -6,7 +6,7 @@ A Ruby library which implements ID3 (information gain) algorithm for decision tr
- Continuous looks at all possible values for a variable and iteratively chooses the best threshold between all possible assignments. This results in a binary tree which is partitioned by the threshold at every step. (e.g. temperate > 20C) - Continuous looks at all possible values for a variable and iteratively chooses the best threshold between all possible assignments. This results in a binary tree which is partitioned by the threshold at every step. (e.g. temperate > 20C)
## Features ## Features
- ID3 algorithms for continuous and discrete cases, with support for incosistent datasets. - ID3 algorithms for continuous and discrete cases, with support for inconsistent datasets.
- Graphviz component to visualize the learned tree (http://rockit.sourceforge.net/subprojects/graphr/) - Graphviz component to visualize the learned tree (http://rockit.sourceforge.net/subprojects/graphr/)
- Support for multiple, and symbolic outputs and graphing of continuos trees. - Support for multiple, and symbolic outputs and graphing of continuos trees.
- Returns default value when no branches are suitable for input - Returns default value when no branches are suitable for input