Implementation of Auto Associative Kernel Regression (AAKR)
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.
pip install aakr
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)
Jesse Myrberg (firstname.lastname@example.org)
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