Application of Decision Tree C5.0, Random Forest, K-NN, Artificial Neural Network, Naive-Bayes algorithms in a Project using R
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Updated
Dec 28, 2015 - R
Application of Decision Tree C5.0, Random Forest, K-NN, Artificial Neural Network, Naive-Bayes algorithms in a Project using R
🍷 CS559/659 Machine Learning Final Project on Predicting Wine Quality
Machine Learning exercises for my subject of Machine Learning at University of Granada (UGR).
Shiny app que emplea SVM sobre datos de entrenamiento
R codes for common Machine Learning Algorithms
SVM app
Hasil Kodingan Pengenalan Pola (R Programming) di IPB
R exercises (2016)
The Fashion-MNIST dataset and machine learning models.
Minimal methylation classifier (MIMIC): A novel method for derivation and rapid diagnostic detection of disease-associated DNA methylation signatures - We describe the development and validation of minimal methylation classifier (MIMIC), combining CpG signature design from genome-wide datasets, multiplex-PCR and detection by single-base extensio…
Statistical Learning with R
Support vector machines flexible framework
Case Study Based on Human Activity Recognition Using Smartphones Dataset
Developed a predictive model that accurately classifies risk using a more automated approach.
Training and tuning of SVM kernels using the classic MNIST dataset in R
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