PHOTON
AI
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Getting Started
Pipeline Architecture
Examples
Features
Algorithms
API
About
PHOTON
AI
Getting Started
Getting Started
Basic Usage
PHOTONAI Framework
A first regression example
Access established ml-packages
Hyperparameter Optimization
Include custom algorithm
Inspect and visualize results
Pipeline Architecture
Pipeline Architecture
Switch (OR)
Stack (AND)
Feature Subset Pipelines
Classifier Ensemble
Examples
Examples
General
General
Simple Classification
Simple Regression
Compare estimators
Over- /Undersampling
Remove confounders
Use a DNN with multiclass prediction
Specific Use Cases
Specific Use Cases
Sample Pairing
No Hyperparameter Optimization
Use site-specific validation
Permutation Importances
Optimize a MLP
Features
Features
Custom Metrics
Hyperparameter Optimization Shortcuts
Load and use a .photon model
Stream additional data
Inspect the dataflow at runtime
Caching
Transform in Batches
Learning Curves
Result Queries
Preprocessing
Algorithms
Algorithms
Access pre-registered algorithms
Transformers
Estimators
Hyperparameter Optimizers
Registry
API
API
Overview
Base
Base
Branch
Hyperpipe
OutputSettings
PipelineElement
Preprocessing
Registry
Stack
Switch
Modelwrapper
Modelwrapper
BaseModelWrapper
Feature Selection
Feature Selection
FClassifSelectPercentile
FRegressionFilterPValue
FRegressionSelectPercentile
LassoFeatureSelection
ModelSelector
Keras
Keras
KerasDnnClassifier
KerasDnnRegressor
LabelEncoder
ImbalancedDataTransformer
Optimization
Optimization
GridSearch
RandomGridSearch
RandomSearch
Scikit-Optimize
SMAC
Nevergrad
Hyperparameter
Hyperparameter
BooleanSwitch
Categorical
FloatRange
IntegerRange
Processing
Processing
Results Handler
Custom Elements
Custom Elements
Custom Transformer
Custom Estimator
About
About
Website
Preprint
Contributions
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