PheKnowLator
benchmarks
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PheKnowLator | benchmarks | |
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1 | 2 | |
138 | 4 | |
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5.8 | 1.8 | |
18 days ago | over 2 years ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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PheKnowLator
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Rosey the Robot
Workflow was built for the PheKnowLator Project
benchmarks
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Forecast Metro Traffic using MindsDB Cloud and MongoDB Atlas
We will be using the Metro traffic dataset 🚇 that can be downloaded from here. You are also free to use your own dataset and follow along the tutorial.
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Launch HN: MindsDB (YC W20) – Machine Learning Inside Your Database
Regrading benchmarks, we have three main dataset collections we focus on currently:
1. Datasets from customers, but obviously those can’t be made public.
2. The OpenML benchmark, which is fairly limited because it’s mainly binary categories, but which is good because it’s a 3rd party, so unbiased. We have some intermediary results here (https://docs.google.com/spreadsheets/d/1oAgzzDyBqgmSNC6g9CFO...) , they are middle-of-the-road. However I think the benchmark is pretty limited, i.e. it doesn’t cover most of the kinds of inputs and almost none of the output we support
3. An internal benchmark suite which currently has 59 datasets, mainly focused around classification and regression tasks with many inputs, timeseries problems and text. Some part of it is public but opening that up is a bit difficult due to licensing issues. I’m hoping that in the next year it will grow and 90%+ of it can be made public. We benchmarkagainst older versions of mindsdb, against hand made models we try to adapt to the task, against the state of the art accuracy for the dataset (if we can find it) and a few other auto ML frameworks (well, 1, but I hope to extend that list) [see this repo for the ones we made public: https://github.com/mindsdb/benchmarks, but I'm afraid it's a bit outdated]
That being said benchmarking for us is still WIP, since as far as I can tell nobody is trying to build open source models that are as broad as what we're currently doing (for better or worst), and the closed source services offered by various IaaS providers don't really come with public benchmark results outside of marketing.
What are some alternatives?
Rotten-Scripts - Scripts that will make you go WOW!
MindsDB - The platform for customizing AI from enterprise data
extruct - Extract embedded metadata from HTML markup
kraken - OCR engine for all the languages
LinkedDataHub - The low-code Knowledge Graph application platform. Apache license.
OMOP2OBO - OMOP2OBO: A Python Library for mapping OMOP standardized clinical terminologies to Open Biomedical Ontologies
contextualise - Contextualise is an effective tool particularly suited for organising information-heavy projects and activities consisting of unstructured and widely diverse data and information resources
topic-db - TopicDB is a topic maps-based semantic graph store (using SQLite for persistence)
foodon - The core repository for the FOODON food ontology project. This holds the key classes of the ontology; larger files and the results of text-mining projects will be stored in other repos.