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r_emailclassify

A Practice of Mail Classifier Using R Language

r_recommendation_system

Data and code for the Dataists R recommendation system contest

r_text_mining

Beginner-Level Text-Mining of Conference Abstracts

rmsc4001

Codes for RMSC4001@CUHK

rugs-meetup

R code for my presentation at R User Group Singapore

s-maps

R code/package for nonlinear forecasting and regime shift detecting

salary_prediction

Using job descriptions from UK, we predict the salaries for the job using text and data mining techniques

sbwfire

Interactions between SBW and Fire

shinyapps

Deploy Shiny applications to ShinyApps

smappr

R tools for analysis of Twitter data

sociothese

Topic models for @coulmont.

spam-detector

R code - machine learning spam detector

spam_detection

R code implementing logistic regression, linear discriminant analysis, decision trees, bagging and random forest to classify email between good ones and spams

spotfire

R code share

sta250_final

Code, report, and data for classifying a large number of images into two categories.

starwars

Visualizing Star Wars scripts with arc diagrams

stat4400

R code for Statistical Machine Learning

statistical_inference

stumbleupon

StumbleUpon challenge

stumbleupon-1

https://www.kaggle.com/c/stumbleupon

supermicar

Word lists for classifying drug names from SuperMICAR text entries, and SAS and R scripts for analysing that data.

swirl_courses

A collection of interactive courses for the swirl R package.

terraform-azurerm-policy-as-code

Terraform modules for managing the lifecycle of custom Azure Policies

test-repo

This is a test repo

testapp

Testing errors for Text analysis Shiny App

text-analytics

Work done for Text Analytics course

text-classification-using-kernel-methods

Text Classification Using Kernel Methods with tm, kernlab and snowball.

text-mining

Introduction to Text Mining in R script from presentation at UPSTAT

text-mining-using-r

Classifying documents into categories

text-mining-weak-signals

This is a collection of mostly R code to use text mining to analyse conference abstracts, blogs and other sources in an attempt to look for "weak signals" (early signs of new trends), See the wiki pages for background etc.