R packages Implementing linear models for classification
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Updated
Aug 21, 2017 - R
R packages Implementing linear models for classification
Various techniques applied for the prediction of bankruptcy- Generalized Linear Regression- Logistic, Classification Tree, Generalized Additive Model, Linear Discriminant Analysis and Neural Networks. Evaluation criteria used was misclassifcation errors.
Portfolio of machine learning projects
Multivariate Environmental Statistics (BEE6300) R Code
Six machine learning models for predicting bladder cancer progression using Caret package
A Survey on ML Techniques for Airbnb Price Prediction
Machine Learning: Group Project
In this project we can see in action and in detail a big part of the ML pipeline (data wrangling,model building, model evaluation) that comprises different algorithms and approaches such as Decision Trees (RPART), Linear Discriminant Analysis (LDA), Gradient Boosting Machne (GBM), Random Forest (RF) Support Vector Machine (SVM) with or without M…
Supervised learning and unsupervised in R, with a focus on regression and classification methods.
Training ensemble machine learning classifiers, with flexible templates for repeated cross-validation and parameter tuning
Exploring American beliefs in the COVID-19 conspiracy theory – Coronavirus is a Chinese bioweapon.
R | Classification Project
A Data Science Portfolio for potentially interested employers and recruiters.
Multi-sample Unified Discriminant ANalysis
This repository showcases project to predict the likelihood of borrowers defaulting on a loan using Machine Learning models. The task is to perform binary classification to classify borrowers as "will default" or "will not default". An Excel sheet calculates bank profits using these predictive models.
A workflow to understand the changes in expression levels of epithelial cells in smokers.
Bunch of exercises computed during the Machine Learning for Finance course.
Source code written in R to implement multivariate analysis methods. Covering principal component analysist, factor analysist, clustering, manova, and so on.
Tools created for machine learning classification model evaluation
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