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logisticsregression

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Mishaa931 / Truth-Guard

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This repository contains code for evaluating different machine learning models for classifying fake news. The dataset used for this evaluation consists of labeled news articles as either "REAL" or "FAKE". Three popular classifiers, Support Vector Machine (SVM), Decision Tree, and Logistic Regression, are trained and evaluated on this dataset.

nlp svm datavisualization decisiontree confusionmatrix logisticsregression modelevaluation fakenewsdataset
  • Updated Jul 22, 2023
  • Jupyter Notebook

Ava33343 / Risky_Business

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Machine learning for credit card default. Precision-recalls are calculated due to imbalanced data. Confusion matrices and test statistics are compared with each other based on Logit over and under-sampling methods, decision tree, SVM, ensemble learning using Random Forest, Ada Boost and Gradient Boosting. Easy Ensemble AdaBoost classifier appear…

machine-learning svm scikit-learn ensemble-learning confusion-matrix adaboost decision-trees gradient-boosting statstics false-positive random-forest-classifier false-negative logisticsregression roc-curves recall-precision smoteenn smote-oversampler
  • Updated Jul 24, 2020
  • Jupyter Notebook

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