adapt

Installation

  • Installation
  • Github

Tutorials

  • Choosing the right algorithm
  • Quick-Start

API Documentation

  • Feature-based
    • FA
    • CORAL
    • SA
    • fMMD
    • DeepCORAL
    • DANN
    • ADDA
    • WDGRL
    • CDAN
    • MCD
    • MDD
    • CCSA
  • Instance-based
    • LDM
    • KLIEP
    • KMM
    • NearestNeighborsWeighting
    • TrAdaBoost
    • TrAdaBoostR2
    • TwoStageTrAdaBoostR2
    • WANN
  • Parameter-based
    • RegularTransferLR
    • RegularTransferLC
    • RegularTransferNN
    • FineTuning
    • TransferTreeClassifier
    • TransferForestClassifier
  • Metrics
    • make_uda_scorer
    • cov_distance
    • neg_j_score
    • linear_discrepancy
    • normalized_linear_discrepancy
    • frechet_distance
    • normalized_frechet_distance
    • domain_classifier
    • reverse_validation
  • Utility Functions
    • UpdateLambda
    • accuracy
    • check_arrays
    • check_estimator
    • check_network
    • get_default_encoder
    • get_default_task
    • get_default_discriminator
    • GradientHandler
    • make_classification_da
    • make_regression_da
    • check_sample_weight
    • set_random_seed
    • check_fitted_estimator
    • check_fitted_network

Synthetic Examples

  • Classification
    • Experimental Setup
    • Src Only
    • DANN
    • Instance Based
  • Two Moons
    • Setup
    • Network
    • Source Only
    • DANN
    • ADDA
    • DeepCORAL
    • CORAL
    • MCD
    • MDD
    • WDGRL
    • CDAN
  • Rotation
    • Setup
    • Source Only
    • CORAL
    • DANN
    • ADDA
  • Toy Regression
    • Experimental Setup
    • TGT Only
    • Src Only
    • All
    • CORAL
    • TrAdaBoostR2
    • RegularTransferNN
  • Sample Bias 1D
    • Setup
    • KMM
    • KLIEP
  • Sample Bias 2D
    • Setup
    • Estimator
    • Source Only
    • KMM
    • KLIEP
  • Multi-Fidelity
    • Setup
    • Network
    • Low fidelity only
    • High fidelity only
    • RegularTransferNN

Real Examples

  • Sample Bias
    • Diabetes Dataset
    • Sample bias correction
    • Features importance
  • Fine-Tuning
    • Train from Scratch
    • Model-based Transfer
  • Deep Domain Adaptation
    • Dataset Preprocessing
    • Fit without adaptation
    • Fit with adaptation
  • TrAdaBoost Experiments
    • Mushrooms
    • 20-NewsGroup
adapt
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© Copyright 2020, ADAPT team, Michelin and Centre Borelli, ENS Paris-Saclay.

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