Search Results for "fuzzy decision tree"
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Showing 3 open source projects for "fuzzy decision tree"
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Get full visibility and control over your tasks and projects with Wrike.Wrike offers world-class features that empower cross-functional, distributed, or growing teams take their projects from the initial request stage all the way to tracking work progress and reporting results.
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EHS Software and Management SystemERA Environmental Software Solutions develops web-based EHS management software for small, medium, and large manufacturers needing to comply with federal, provincial, and state regulations, monitor their air, water, and waste emissions and other environmental outputs, author and manage Safety Data Sheets (SDS) in more than 40 languages, or standardize their Health and Safety procedures for incident and inspection tracking, training delivery, and audit management. The platform also supports comprehensive reporting for programs like TRI, Tier II, Title V, NEI, and NPRI. Companies across the automotive, aerospace, general manufacturing, and paints and coatings industries, to name a few, rely on ERA’s all-in-one, SOC 2 Type II certified SaaS for complete coverage of their EHS needs.
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typewriter-net
It's a plain text editor with vi-mode
This editor has some features from Notepad++, Sublime Text and Vim. The Typewriter.NET has no plugins, but has a simple way to run external scripts, navigate to output error and change text by external scripts. The main idea is make to possible work without mouse (and without arrows in vi-mode) https://github.com/cser/typewriter-net/wiki/Features -
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The PCI toolkit is based on a decision tree assessment methodology, which helps you identify if your web applications are part of the PCI-DSS scope and how to apply the PCI-DSS requirements. By decomposing , one by one , you will be able to create an assessment and a final report of your scope delimitation and which OWASP guidelines must be used
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Medical Datasets (In a text file, with space separated values) can be loaded to the system. By choosing either one of the two classifiers, Neural network or Decision Tree, the system can be trained and evaluated.
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