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lhenry15
10a4f0dd78
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5 years ago | |
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| axolotl | 5 years ago | |
| examples | 5 years ago | |
| images | 5 years ago | |
| tests | 5 years ago | |
| .gitignore | 5 years ago | |
| .gitlab-ci.yml | 5 years ago | |
| .gitmodules | 5 years ago | |
| LICENSE | 5 years ago | |
| README.md | 5 years ago | |
| failed_installation_repos.txt | 5 years ago | |
| run_tests.py | 5 years ago | |
| setup.py | 5 years ago | |
README.md
Axolotl
This package provides an easy and high level abstraction
of the D3M API for AutoML. It contains a suit of basic
requirements and building blocks
primitives.
Installation
The package contains two different version of dependencies,
one with GPU support and other that uses CPU. For the installation
we strongly encourage the use of a python 3.6 virtual environment.
- CPU version.
pip3 install -e git+https://gitlab.com/axolotl1/axolotl.git@devel#egg=axolotl[cpu]
- GPU version.
pip3 install -e git+https://gitlab.com/axolotl1/axolotl.git@devel#egg=axolotl[gpu]
Note:
For MacOs, pycurls needs to be manually installed:
PYCURL_SSL_LIBRARY=openssl LDFLAGS="-L/usr/local/opt/openssl/lib" CPPFLAGS="-I/usr/local/opt/openssl/include" pip install --no-cache-dir pycurl==7.43.0.3
Usage
For new users we recommend installing the package and then cloning it via
git clone --recursive https://gitlab.com/axolotl1/axolotl.git
Then start jupyter lab via
jupyter lab
And then open the examples
directory and try to run them.
全栈的自动化机器学习系统，主要针对多变量时间序列数据的异常检测。TODS提供了详尽的用于构建基于机器学习的异常检测系统的模块，它们包括：数据处理（data processing），时间序列处理（ time series processing），特征分析（feature analysis)，检测算法（detection algorithms），和强化模块（ reinforcement module）。这些模块所提供的功能包括常见的数据预处理、时间序列数据的平滑或变换，从时域或频域中抽取特征、多种多样的检测算
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