ROC-GLM and calibration analysis for DataSHIELD

🔤 ASCII string types for Roc

Technical indicators to run technical analysis with JavaScript & TypeScript. 📈

This module allows users to analyze k-means & hierarchical clustering, and visualize results of Principal Component, Correspondence Analysis, Discriminant analysis, Decision tree, Multidimensional scaling, Multiple Factor Analysis, Machine learning, and Prophet analysis.

📏 Type-safe units of measure in Roc

Software Design by Example in Roc

🌐 A library to create HTML in Roc

🧮 Mathematical functions and constants in Roc

Evaluation of 3D detection and diagnosis performance —geared towards prostate cancer detection in MRI.

ROC methodology explained with R-examples

Experiments with Harmony

🕒 A work in progress Roc library for working with dates and times

An image library that supports exporting to PNG.

Display and analyze ROC curves in R and S+

Raisin Class Prediction

Práctica de clasificación con Machine Learning en el dataset del Titanic, abordando exploración de datos, preprocesamiento, selección de métricas y modelos, con el objetivo de analizar detalladamente los resultados obtenidos.

A set of data tools in Python

PyEER is a python package for biometric systems performance evaluation. Includes ROC, DET, FNMR, FMR and CMC curves plotting, scores distribution plotting, EER and operating points estimation. It can be also used to evaluate binary classification systems.

🥠 A replacement for the fortune UNIX command in Roc

Employing advanced techniques, the project seamlessly integrates binary and multiclass classifiers for character classification. It offers a comprehensive analysis and adeptly addresses challenges in the realm of computer vision.This project was part of my uOttawa Master's in Computer Vision course (2023).