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Xpdeep

What is Xpdeep ?
Getting Started
Getting Started
- Installation
- Key Concepts
Dataset
Dataset
Model
Model
- Concept
- Create a Model
Train
Train
- Train an Xpdeep Model
- Learning Curves
Explain
Explain
- Learn a Self-Explainable Model
- Explain an Existing Model
Visualize
Tutorials
Tutorials
- From SOTA to Xpdeep
  From SOTA to Xpdeep
- Case Studies
  Case Studies
- Explain an Existing Model
  Explain an Existing Model
  - Classification - Tabular
  - Object Detection - Image
Changelog
Support
API
API
- xpdeep
  xpdeep
  - client_factory
  - dataset
    
    dataset
    
    feature
    
    feature
    
    abstracts
    
    augmentation
    
    feature
    
    feature_types
    
    parquet_dataset
    
    preprocessor
    
    preprocessor
    
    preprocessor
    
    zoo
    
    zoo
    
    doc
    
    schema
  - explain
    
    explain
    
    explainer
    
    explanation_artifact
    
    quality_metrics
    
    statistic
  - filtering
    
    filtering
    
    criteria
    
    filter
  - initialize
  - metric
  - model
    
    model
    
    feature_extraction_output_type
    
    model_parameters
    
    trained_model_artifact
    
    utils
    
    xpdeep_model
    
    zoo
    
    zoo
    
    cnn
    
    cross_entropy_loss_from_proba
    
    doc
    
    mlp
  - project
  - trainer
    
    trainer
    
    callbacks
    
    trainer
  - utils
    
    utils
    
    api_model_conversion
    
    api_model_conversion
    
    trusted_object
    
    errors
    
    initialized_client_verification
    
    initialized_project_verification
    
    pagination
    
    pipelines
    
    pipelines
    
    explanation_computing
    
    model_training
    
    schema_analysis
    
    schema_fitting

Visualisation Module#

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Explain an Existing Model

Classification - Tabular

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