MIML Learning Library
Project description
miml: Multi Instance Multi Label Learning Library for Python
The aim of the library is to ease the development, testing and comparison of classification algorithms for multi-instance multi-label learning (MIML).
Table of Contents
Installation
Use the package manager pip to install miml.
$ pip install miml-package
Requirements
The requirement packages for miml library are: numpy, scikit-learn, scipy, tensorflow or tensorflow-gpu. Installing miml with the package manager does not install the package dependencies. So install them with the package manager manually if not already downloaded.
$ pip install numpy
$ pip install scikit-learn
$ pip install scipy
$ pip install tensorflow
License
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
mimllearning-0.1.5.tar.gz
(1.1 MB
view hashes)
Built Distribution
mimllearning-0.1.5-py3-none-any.whl
(769.2 kB
view hashes)
Close
Hashes for mimllearning-0.1.5-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9707a97720f842b3345570d751c91c6f01548d78429066df08bc495310a60e35 |
|
MD5 | 3589f9e5aa8952f84a1624078ae1074b |
|
BLAKE2b-256 | 4ca4e4990f0c105cddae035f1371c28c5b26b70a3a3d79c032030a61ea322de8 |