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 stackingEvalML 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 automlFeatures 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-extractionBoruta is an R package implementing Boruta, an all relevant feature selection method. More details here.
boruta feature-selection machine-learning cranA 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 matlabThe 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-applicationEsse 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-selectionFormats 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
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