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bagged-forests

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sakbarpu / TraditionalClassifiers

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This repository implements the basic machine learning classifiers for the problem of Yelp reviews classification. We assume the problem to be a binary classification problem. The models implemented are Naive Bayes, Logistic Regression, Support Vector Machine (linear), Decision Trees, Bagged Decision Trees, Random Fforests, and Boosted Decision T…

random-forest naive-bayes naive-bayes-classifier pca logistic-regression support-vector-machine decision-trees support-vector-machines tsne naive-bayes-algorithm principal-component-analysis boosted-trees naive-bayes-classification bagged-forests
  • Updated May 6, 2018
  • Python

mirugwe1 / Accurate-occupancy-detection-of-an-office-room-from-light-temperature-humidity-and-CO2-measurement

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This project aims at developing, validating, and testing several classification statistical models that could predict whether or not an office room is occupied using several data features, namely temperature (◦C), light (lx), humidity (%), CO2 (ppm), and a humidity ratio. The data is modeled using classification techniques i.e. Logistic regressi…

data-science machine-learning data-mining random-forest exploratory-data-analysis supervised-learning logistic-regression decision-trees data-modeling boosted-trees bagged-forests
  • Updated Dec 21, 2020

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