Releases: mindsdb/lightwood
Releases · mindsdb/lightwood
Release 1.4.0
Lightwood 1.4.0 changelog:
Features:
- Streamlined dynamic
.predict()
argument passing (#563) - Set default logging level with environment variable (@mrandri19, #603)
- Colored logs (@mrandri19, #608)
Bug fixes:
JsonAI
blocks are nowModule
s (#569)- Ignore column drop error if column is not in the dataframe (#579)
- LightGBM dependency issue (#609)
Other
- Introduction to statistical analyzer tutorial (#577)
- Custom cleaner tutorial (#581)
- Custom mixer tutorial (#575)
- Custom analysis block tutorial (#576)
- Docstring for
BaseEncoder
(#587) - Native Jupyter notebook support inside docs (#586)
- Automated docs deployment (#610)
- Updated CLA bot (#612)
- Improved
README.md
andCONTRIBUTING.md
(#613)
Note: benchmarks will not run on the latest commit for this release, they were instead successfully ran for commit 79f27325a0877bb95709373007a97161fc9bb2eb
.
Release 1.3.0
Lightwood 1.3.0 changelog:
Features:
- Modular Cleaner (#538 and #568)
- Modular Analysis (#539)
- Better Imports (#540)
- Improved Json AI default arguments (#543)
- Add seed to splitter (#553)
- Stratification and 3-way splitting (#542, #571)
- Use MASE metric for TS model selection (#499)
Bug fixes:
- Allow quantity as target (#546)
- Fix for LightGBM device check (#544)
- Select OneHotEncoder at Json AI build time and fix pd.None bugs (#549)
- Miscellaneous fixes (#570)
Other
- Improved CONTRIBUTING.md (#550)
Release v1.2.0
Features:
- Better defaults for Neural model in time series tasks (#461)
- Seed keyword passed (#482)
- Handle ' and " in dataset column names (#503)
- Helper function to split grouped time series (#501)
- Enhanced date-time + tag histograms (#502)
- Nonconformist speed optimizations (#497)
- Add
dtype.tsarray
(#530)
Bug fixes:
- Fix analysis memory usage (#485)
- Fix incorrect return value for order column in time series tasks (#488)
- Fix time series encoding issue (#495)
- Remove deprecated logic (#518)
- Make explainer work with categorical targets not present in the training data (#500)
- Fix sktime dependency (#524)
- Better detection, cleaning and encoding of arrays (#512)
- Use correct accuracy score for binary data (#532)
allow_incomplete_history
for time series predictors (#525)