Automated modeling and machine learning framework FEDOT
Minor fixes and improvements.
Full Changelog: https://github.com/aimclub/FEDOT/compare/v0.7.3.1...v0.7.3.2
Minor fixes and improvements, better installation
Hello, AutoML folk! We’re releasing a minor version of FEDOT that includes the following.
PyPi release: https://pypi.org/project/fedot/0.7.3/
Features & Enhancements:
from fedot import Fedot
by @MorrisNein in https://github.com/aimclub/FEDOT/pull/1179
Full Changelog: https://github.com/aimclub/FEDOT/compare/v0.7.2...v0.7.3
Hello, AutoML folk! We’re releasing a minor version of FEDOT that includes the following.
PyPi release: https://pypi.org/project/fedot/0.7.2/
Features & Enhancements:
Bugfixes:
Hello, AutoML folk! We’re releasing a minor version of FEDOT that includes the following.
PyPi release: https://pypi.org/project/fedot/0.7.1/
Features & Enhancements:
Bugfixes:
Hi, folk!
This release marks major change! Our team separated all the core modules (graph, adapter, optimizer, tuner etc.) into the separate project GOLEM (https://github.com/aimclub/GOLEM).
FEDOT now contains modules related to Data handling, preprocessing, machine learning logic like Pipeline (implementation of ML Graph), ML operations, ML metrics.
There're also few other changes:
Hi all!
Importantly, release 0.6.2 marks the last self-sufficient version of FEDOT before transition to GOLEM optimization core (https://github.com/aimclub/GOLEM).
This release introduces a number of API enhancements and several bug fixes. Enhancements:
Bug fixes:
Hi, folk! We're making a new minor release with a number of improvements. This is an important release in a sense that this is a last release of self-contained FEDOT. The next major release will mark a separation of the optimizer core into the separate project.
New features, better quality & changes in API
Enhancements and fixes:
Documentation is extended
Architectural refactorings are continued:
Hi everyone! We released a new major version of FEDOT - 0.6.0
It includes a lot of major changes:
PipelineBuilder
(#597) – that simplifies manual construction of ML Pipelines;Also, this release contains by a lot of architectural refactorings of the framework:
EvoGraphOptimizer
(#687)Objective
& Fitness
(#654) – classes that substitutes simple float
metric values & abstract single vs. multi-objective metricsDataMerger
facilityAlso, there are various bug-fixes related to ML operations, evolutionary operators & internal Graph operations.
The most important changes: