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v0.2.25

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@oguiza oguiza released this 06 Feb 17:22
· 446 commits to main since this release

0.2.25

Breaking Changes

  • updated forward_gaps removing nan_to_num (#331)

  • TSRobustScaler only applied by_var (#329)

  • remove add_na arg from TSCategorize (#327)

New Features

  • added IntraClassCutMix1d (#384)

  • added learn.calibrate_model method (#379)

  • added analyze_array function (#378)

  • Added TSAddNan transform (#376)

  • added dummify function to create dummy data from original data (#366)

  • added Locality Self Attention to TSiT (#363)

  • added sel_vars argument to MVP callback (#349)

  • added sel_vars argument to TSNan2Value (#348)

  • added multiclass, weighted FocalLoss (#346)

  • added TSRollingMean batch transform (#343)

  • added recall_at_specificity metric (#342)

  • added train_metrics argument to ts_learner (#341)

  • added hist to PredictionDynamics for binary classification (#339)

  • add padding_idxs to MultiEmbedding (#330)

Bugs Squashed

  • sort_by data may be duplicated in SlidingWindowPanel (#389)

  • create_script splits the nb name if multiple underscores are used (#385)

  • added torch functional dependency to plot_calibration_curve (#383)

  • issue when setting horizon to 0 in SlidingWindow (#382)

  • replace learn by self in calibrate_model patch (#381)

  • Argument d_head is not used in TSiTPlus (#380)

  • replace default relu activation by gelu in TSiT (#361)

  • sel_vars and sel_steps in TSDatasets and TSDalaloaders don't work when used simultaneously (#347)

  • ShowGraph fails when recoder.train_metrics=True (#340)

  • fixed 'se' always equal to 16 in MLSTM_FCN (#337)

  • ShowGraph doesn't work well when train_metrics=True (#336)

  • TSPositionGaps doesn't work on cuda (#333)

  • XResNet object has no attribute 'backbone' (#332)

  • import InceptionTimePlus in tsai.learner (#328)

  • df2Xy: Format correctly without the need to specify sort_by (#324)

  • bug in MVP code learn.model --> self.learn.model (#323)

  • Colab install issues: importing the lib takes forever (#315)

  • Calling learner.feature_importance on larger than memory dataset causes OOM (#310)