This aims to run a subset selection process on the data set using R
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Updated
Mar 28, 2021 - R
This aims to run a subset selection process on the data set using R
Neighbourhood Functions for Local-Search Algorithms
Data Analytics and Machine Learning in R. Linear-regression, Logistic-regression, Hierarchical-clustering, Boosting, Bagging, Random-forests, K-means-clustering, K-nearest-neighbors (K-N-N), Tree-pruning, Subset-selection, LDA, QDA, Support Vector Machines (SVM)
Fast Backward Elimination in R
Find the simplest model and the best method to predict whether an observation belongs to categories LOWER/GREATER of 20% trimmed mean of "ncrim" variable. AUEB Computer Science course Statistical Learning.
Designing Industrial Experiments, one-way, and two-way ANOVA analysis, Experimental design principles (Replication, Randomization, and Blocking), Parameter Estimation, Sample Variance
A summative coursework for MAS8404 Statistical Learning for Data Science
R package of the Approximate Best Subset Maximum Binary Prediction Rule (PRESCIENCE) proposed by Chen and Lee (2018).
This project is on Data Mining process using R depending on ISLR book.
Efficient Variable Selection for GLMs in R
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