Learn and practice alternative evaluation techniques for models on which more standard accuracy methods are not feasible
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Updated
Mar 17, 2020 - Jupyter Notebook
Learn and practice alternative evaluation techniques for models on which more standard accuracy methods are not feasible
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…
Shiny App to help you generate adjusted ROC curves
An analysis of the 2016 presidential election dataset to predict voter behavior
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MCC-F1 curve implementation in Python
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Knowledge Discovery in Dataset
Using R and machine learning to build a classifier that can detect credit card fraudulent transactions.
Machine Learning analysis for an imbalanced dataset. Developed as final project for the course "Machine Learning and Intelligent Systems" at Eurecom, Sophia Antipolis
The subject of this repository was to perform binary classification based on respondent's collected features (age, cholesterol level, fasting blood sugar, thallium stress test results, etc.).
Wolfram Language (aka Mathematica) paclet for Receiver Operation Characteristic (ROC) functions.
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An education company named X Education sells online courses to industry professionals. On any given day, many professionals who are interested in the courses land on their website and browse for courses.
AUCC (Python Implementation)
Utility function to plot roc curves using k-fold cross-validation
Sub-package of spatstat providing functions for exploratory and nonparametric data analysis
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