machine-learning-in-ebpf
This repository contains the code for the paper "A flow-based IDS using Machine Learning in eBPF", Contact: Maximilian Bachl (by CN-TU)
catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU. (by catboost)
machine-learning-in-ebpf | catboost | |
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3 | 8 | |
76 | 7,753 | |
- | 0.8% | |
4.9 | 9.9 | |
18 days ago | 5 days ago | |
C | Python | |
GNU General Public License v3.0 only | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
machine-learning-in-ebpf
Posts with mentions or reviews of machine-learning-in-ebpf.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-12-22.
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Show HN: eBPF-powered L4 package dropper
I meant Transport Layer packages.
> https://github.com/CN-TU/machine-learning-in-ebpf
Thank you! I'll take a look.
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A flow-based IDS using Machine Learning in eBPF
I’m not the post other but a coauthor of the paper. If there are some details missing in the paper, there’s also the open source implementation, also referenced in the paper: https://github.com/CN-TU/machine-learning-in-ebpf
catboost
Posts with mentions or reviews of catboost.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-07-05.
- CatBoost: Open-source gradient boosting library
- Boosting Algorithms
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What's New with AWS: Amazon SageMaker built-in algorithms now provides four new Tabular Data Modeling Algorithms
CatBoost is another popular and high-performance open-source implementation of the Gradient Boosting Decision Tree (GBDT). To learn how to use this algorithm, please see example notebooks for Classification and Regression.
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Writing the fastest GBDT libary in Rust
Here are our benchmarks on training time comparing Tangram's Gradient Boosted Decision Tree Library to LightGBM, XGBoost, CatBoost, and sklearn.
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Data Science toolset summary from 2021
Catboost - CatBoost is an open-source software library developed by Yandex. It provides a gradient boosting framework which attempts to solve for Categorical features using a permutation driven alternative compared to the classical algorithm. Link - https://catboost.ai/
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CatBoost Quickstart — ML Classification
CatBoost is an open source algorithm based on gradient boosted decision trees. It supports numerical, categorical and text features. Check out the docs.
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[D] What are your favorite Random Forest implementations that support categoricals
If you considering GBDT check out catboost, unfortunately RF mode is not available but library implement lots of interesting categorical encoding tricks that boost accuracy.
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CatBoost and Water Pumps
The data contains a large number of categorical features. The most suitable for obtaining a base-line model, in my opinion, is CatBoost. It is a high-performance, open-source library for gradient boosting on decision trees.