An expectation-maximization algorithm for finding noninvadable stationary states. by Robert Marsland (8616483)

“…<i>(c)</i> Pseudocode for self-consistently computing <b>R</b>* and , which is identical to standard expectation-maximization algorithms employed for problems with latent variables in machine learning.…”

Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

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Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

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Python cv coding screenshots of all developed fingerprints on distinct surfaces. by Nisha Yadav (366131)

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Code snippets to add user-specific custom functionality in PyNoetic. by Gursimran Singh (575288)

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Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

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Python-based Monte Carlo Simulation Tool by Yangfan Jiang (9372782)

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. by Gursimran Singh (575288)

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ROC analysis of the Machine Learning Algorithm. by Stephan Ellmann (314565)

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WGCNA and machine learning algorithms. by Shushu Wang (6870191)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

“…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …”

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

“…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…”

Data_Sheet_1_Decoding emotional resilience in aging: unveiling the interplay between daily functioning and emotional health.PDF by Minhua Guo (18392646)

Performances of Naïve Bayes (NB), Multilayer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), Support Vector Machine (SVM) and K- Nearest Neighbors (KNN). by Solomon Shiferaw Beyene (9143178)

PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

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Machine learning algorithm parameters. by Namal Rathnayake (15361124)

Comparison of algorithms in two cases. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Flow of the NSGA-II algorithm. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

A Python Package for the Localization of Protein Modifications in Mass Spectrometry Data by Anthony S. Barente (14035175)

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