deslib
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  • User guide
  • API Reference
  • General examples
    • Simple example
    • Measuring the influence of the region of competence
    • Dynamic selection vs K-NN: Using instance hardness
    • Calibrating base classifiers to estimate probabilities
    • Using the Dynamic Frienemy Pruning (DFP)
    • Comparing dynamic selection with baseline static methods
    • Comparing dynamic selection with Random Forest
    • Example using heterogeneous ensemble
    • Dynamic selection with linear classifiers: XOR example
    • Visualizing decision boundaries on the P2 problem
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General examplesΒΆ

Examples showing how to use different aspect of the library

Simple example

Simple example

Measuring the influence of the region of competence

Measuring the influence of the region of competence

Dynamic selection vs K-NN: Using instance hardness

Dynamic selection vs K-NN: Using instance hardness

Calibrating base classifiers to estimate probabilities

Calibrating base classifiers to estimate probabilities

Using the Dynamic Frienemy Pruning (DFP)

Using the Dynamic Frienemy Pruning (DFP)

Comparing dynamic selection with baseline static methods

Comparing dynamic selection with baseline static methods

Comparing dynamic selection with Random Forest

Comparing dynamic selection with Random Forest

Example using heterogeneous ensemble

Example using heterogeneous ensemble

Dynamic selection with linear classifiers: XOR example

Dynamic selection with linear classifiers: XOR example

Visualizing decision boundaries on the P2 problem

Visualizing decision boundaries on the P2 problem

Download all examples in Python source code: auto_examples_python.zip
Download all examples in Jupyter notebooks: auto_examples_jupyter.zip

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© Copyright 2018, Rafael M. O. Cruz Revision 9bf94ef7.

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