mlr - mlr: Machine Learning in R

•    R

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Please cite our JMLR paper [bibtex]. Some parts of the package were created as part of other publications. If you use these parts, please cite the relevant work appropriately. An overview of all mlr related publications can be found here.

machine-learning data-science tuning cran r-package predictive-modeling classification regression statistics r survival-analysis imbalance-correction tutorial mlr learners hyperparameters-optimization feature-selection multilabel-classification clustering stacking

evalml - EvalML is an AutoML library written in python.

•    Python

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EvalML is an AutoML library which builds, optimizes, and evaluates machine learning pipelines using domain-specific objective functions.

data-science machine-learning optimization feature-selection model-selection feature-engineering hyperparameter-tuning automl

Feature-Selection - Features selection algorithm based on the self selected-algorithm, loss function and validation method

•    Python

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Features selection algorithm based on the self selected-algorithm, loss function and validation method

machine-learning feature-engineering feature-selection data-science greedy-search feature-importance feature-extraction

Boruta - Boruta R package

•    R

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Boruta is an R package implementing Boruta, an all relevant feature selection method. More details here.

boruta feature-selection machine-learning cran

FEAST - A FEAture Selection Toolbox for C/C+, Java, and Matlab/Octave.

•    C

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A FEAture Selection Toolbox for C/C++ & MATLAB/OCTAVE, v2.0.0. If you use these implementations for academic research please cite the relevant paper above. All FEAST code is licensed under the BSD 3-Clause License.

feature-selection matlab

DocumentFeatureSelection - A set of metrics for feature selection from text data

•    Python

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The feature selection is also useful when you observe your text data. With the feature selection, you can get to know which features really contribute to specific labels. Please visit project page on github.

nlp feature-selection feature-extraction python-3 pmi tf-idf bns soa docker webapp web-app web-application flask-application

Machine_Learning - Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks

•    Jupyter

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Esse repositório foi criado com a intenção de difundir o ensino de Machine Learning em português. Os algoritmos aqui implementados não são otimizados e foram implementados visando o fácil entendimento. Portanto, não devem ser utilizados para fins de pesquisa ou outros fins além dos especificados.

machine-learning machine-learning-algorithms adaboost decision-trees kmeans knn linear-discriminant-analysis principal-component-analysis naive-bayes regression linear-regression neural-network redes-neurais-artificiais multilinear-regression polynomial-regression feature-selection

data-formatter - Takes raw csv input and formats it to be ready for neural networks

•    Python

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Formats and cleans your data to get it ready for machine learning!

neural-network machine-learning data-formatting normalization min-max-normalization min-max-normalizing brain.js automated-machine-learning bestbrain data-science kaggle scikit-learn sklearn scikit-neuralnetworks lasagne nolearn nolearn.lasagne data-cleaning data-munging data-preparation imputing-missing-values filling-in-missing-values dataset data-set training testing random-forest vectorization categorization one-hot-encoding dictvectorizer preprocessing feature-selection feature-engineering