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Contents:

  • How to use DIANNA
  • Why DIANNA?
  • Current and planned DIANNA developments
  • Contributing guidelines
  • Developer documentation for the DIANNA project
  • Contributor Covenant Code of Conduct

Examples

  • General overview of using dianna
  • Interpreting a leaf identification model with LIME
  • Model Interpretation using LIME for penguin dataset classifier
  • Interpreting a weather classification model with LIME
  • Model Interpretation for Pretrained Binary MNIST Model using KernelSHAP
  • Model Interpretation for Pretrained Model to Recognize Geometric Shapes using KernelSHAP
  • Model Interpretation using KernelSHAP for weather prediction regressor
  • Interpreting a movie review sentiment model with RISE
  • Model Interpretation for Pretrained ImageNet Model using RISE
  • Model interpretation using RISE for astronomical timeseries data
  • Interpreting the sentence classification of legal texts using LIME
  • Model Interpretation using LIME for penguin dataset classifier
  • API Reference
dianna
  • Python Module Index

Python Module Index

_ | d | h | i | k | l | r | t
 
_
_image_utils
_model_utils
_models_image
_models_tabular
_models_text
_models_ts
_movie_model
_shared
_ts_utils
 
d
- dianna
    dianna._logging_utils
    dianna.cli
    dianna.utils
    dianna.utils.downloader
    dianna.utils.maskers
    dianna.utils.misc
    dianna.utils.onnx_runner
    dianna.utils.predict
    dianna.utils.rise_utils
    dianna.utils.tokenizers
    dianna.visualization
    dianna.visualization.image
    dianna.visualization.tabular
    dianna.visualization.text
    dianna.visualization.timeseries
 
h
Home
 
i
Images
 
k
kernelshap_image
kernelshap_tabular
 
l
lime_image
lime_tabular
lime_text
lime_timeseries
 
r
rise_image
rise_tabular
rise_text
rise_timeseries
 
t
Tabular
Text
Time_series

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