scorystal alternatives and similar shards
Based on the "Science and Data analysis" category.
Alternatively, view scorystal alternatives based on common mentions on social networks and blogs.
-
ishi
Graph plotting package with a small API and sensible defaults powered by gnuplot. -
stats
An expressive crystal implementation of statistical distributions and usual math functions. :bar_chart: -
predict.cr
Satellite prediction library for crystal using the sgp4 model -
chizge
A Network (Graph) Analysis library for Crystal Language, inspired by NetworkX. -
alea
Repeatable pseudo-random sampling, CDF over most known probability distributions.
Build time-series-based applications quickly and at scale.
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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README
Scorystal
Crystal scoring API for Predictive Model Markup Language (PMML).
Currently supports random forest and gradient boosted models.
Will be happy to implement new kinds of models by demand, or assist with any other issue.
Contact me here or at [email protected].
Installation
Add this to your application's shard.yml
:
dependencies:
scorystal:
github: asafschers/scorystal
Usage
require "scorystal"
# Parse PMML file
pmml_text = File.read("spec/pmmls/gbm.pmml")
parsed_pmml = XML.parse(pmml_text, XML::ParserOptions::NOBLANKS)
# Set features hash
json = %({"F1":null,"F2":21371,"F3":"AA"}")
features = Scorystal.features_hash(json)
# Gradient Boosted Model
gbm = Gbm.new(parsed_pmml)
puts gbm.score(features)
# Random Forest
rf = RandomForest.new(parsed_pmml)
puts rf.decisions_count(features)
Contributing
- Fork it ( https://github.com/asafschers/scorystal/fork )
- Create your feature branch (git checkout -b my-new-feature)
- Commit your changes (git commit -am 'Add some feature')
- Push to the branch (git push origin my-new-feature)
- Create a new Pull Request
Contributors
- [asafschers] asaf schers - creator, maintainer