Pattern-based Embedding for Time Series Classification

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PETSC

Pattern-based Embedding for Time Series Classification (PETSC).

This repository contains a Python/C++ implementation of PETSC, that is compatible with aeon. Two variants of PETSC are supported as well: MR-PETSC and PETSC-SOFT.

Installation

The easiest way to install petsc-ts is via pip:

pip install petsc-ts

If you want to run the tests locally (currently only an aeon test to check if the estimator complies with the required format), install the optional dependency:

pip install "petsc-ts[test]"

You can then import the PetsClassifier class as follows and use it as any other scikit-learn-compatible estimator:

from petsc_ts.classifier import PetsClassifier

clsf = PetsClassifier()
clsf.fit(X_train, y_train)
clsf.predict(X_test)
clsf.predict_proba(X_test)

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1.4

1.3

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1.2

1.1

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The following attestation bundles were made for petsc_ts-1.2-cp39-cp39-macosx_11_0_arm64.whl:

Publisher: build_wheels.yml on steenrotsman/petsc-ts

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Provenance

The following attestation bundles were made for petsc_ts-1.2-cp39-cp39-macosx_10_9_x86_64.whl:

Publisher: build_wheels.yml on steenrotsman/petsc-ts

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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