Releases: jeongyoonlee/Kaggler
Releases · jeongyoonlee/Kaggler
v0.9.15
What's Changed
- Fix
AutoLGB. Reformat withblackby @jeongyoonlee in #71 - up the version to 0.9.15 by @jeongyoonlee in #73
- Update
test.ymlby @jeongyoonlee in #69 - Update
python-publish.ymlby @jeongyoonlee in #70
Full Changelog: v0.9.14...v0.9.15
v0.9.14
What's Changed
- Update
python-publish.ymlby @jeongyoonlee in #64 - add
plot_curve()for plotting ROC and PR curves by @jeongyoonlee in #66 - fix build error by replacing
ml_metrics's kappa withscikit-learn's by @jeongyoonlee in #67 - up the version to 0.9.14 by @jeongyoonlee in #68
Full Changelog: v0.9.13...v0.9.14
v0.9.13
- add transfer learning with the
pretrained_modelinput argument - allow to set the learning_rate in
__init__() - add a test for transfer learning between
DAE/SDAE
v0.9.12
- make
label_encoding=Truedefault inDAE/SDAE
v0.9.11
- fix an error raised when printing out the
DAE/SDAEobjects - update
random_state/seedarguments inDAE/SDAE/DAELayerto followscikit-learn/tensorflowconventions - up the version to v0.9.11
v0.9.10
- add options to add more than 1 encoder in
DAELayer - add options to add
validation_datainDAE/SDAE - make label-encoding optional in
DAE/SDAE
v0.9.9
v0.9.8
- hotfix
SDAE
v0.9.7
- add
SDAE, supervised denoising AutoEncoder
v0.9.5
- copy dataframe before transforming it in encoders to prevent overwriting
- update the default threshold for feature selection in automl
- fix DAE with all numeric features