[pre-commit.ci] pre-commit autoupdate (#7387) · zinating/algorithms-python@0c7c5fa · GitHub
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[pre-commit.ci] pre-commit autoupdate (TheAlgorithms#7387)
* [pre-commit.ci] pre-commit autoupdate updates: - [github.com/asottile/pyupgrade: v3.0.0 → v3.1.0](asottile/pyupgrade@v3.0.0...v3.1.0) - [github.com/codespell-project/codespell: v2.2.1 → v2.2.2](codespell-project/codespell@v2.2.1...v2.2.2) * updating DIRECTORY.md * Fix typo discovered by codespell * Fix typo discovered by codespell * Update .pre-commit-config.yaml * Update .pre-commit-config.yaml * Update .pre-commit-config.yaml Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com> Co-authored-by: Christian Clauss <cclauss@me.com>
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‎.pre-commit-config.yaml‎

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‎DIRECTORY.md‎

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* [Tower Of Hanoi](other/tower_of_hanoi.py)
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## Physics
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* [Casimir Effect](physics/casimir_effect.py)
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* [Horizontal Projectile Motion](physics/horizontal_projectile_motion.py)
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* [Lorentz Transformation Four Vector](physics/lorentz_transformation_four_vector.py)
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* [N Body Simulation](physics/n_body_simulation.py)
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* [Deutsch Jozsa](quantum/deutsch_jozsa.py)
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* [Half Adder](quantum/half_adder.py)
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* [Not Gate](quantum/not_gate.py)
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* [Q Full Adder](quantum/q_full_adder.py)
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* [Quantum Entanglement](quantum/quantum_entanglement.py)
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* [Ripple Adder Classic](quantum/ripple_adder_classic.py)
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* [Single Qubit Measure](quantum/single_qubit_measure.py)

‎machine_learning/local_weighted_learning/local_weighted_learning.md‎

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So, here comes the role of non-parametric algorithm which doesn't compute predictions based on fixed set of params. Rather parameters $\theta$ are computed individually for each query point/data point x.
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While Computing $\theta$ , a higher "preferance" is given to points in the vicinity of x than points farther from x.
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While Computing $\theta$ , a higher preference is given to points in the vicinity of x than points farther from x.
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Cost Function J($\theta$) = $\sum_{i=1}^m$ $w^i$ (($\theta$)$^T$ $x^i$ - $y^i$)$^2$
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‎maths/is_square_free.py‎

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