Implementation of Auto Associative Kernel Regression (AAKR)
Project description
aakr (Auto Associative Kernel Regression)
aakr is a Python implementation of the Auto-Associative Kernel Regression (AAKR). The algorithm is suitable for signal reconstruction, which can further be used for condition monitoring, anomaly detection etc.
Documentation is available at https://aakr.readthedocs.io.
Installation
pip install aakr
Quickstart
Given historical normal condition X_nc
examples and new observations X_obs
of size n_samples x n_features
, what values we expect to see in normal conditions for the new observations?
from aakr import AAKR
# Create AAKR model
aakr = AAKR()
# Fit the model with normal condition examples
aakr.fit(X_nc)
# Ask for values expected to be seen in normal conditions
X_obs_nc = aakr.transform(X_obs)
References
Jesse Myrberg (jesse.myrberg@gmail.com)
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