R Topics

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R Topics:

Twitter/Text Mining:
For text analysis, check out the series in Python, here.

1. Visualizing Twitter Tokens- Hashtags, Smileys and URLs
2. Text Mining: 1. Retrieving Text from Twitter in R Using the twitteR Package *Updated 2014/3/20*
3. Text Mining: 2. Converting Tweet Text List into a Document Corpus with Transformations
4. Text Mining: 3. Stemming Text and Building a Term Document Matrix
5. Text Mining: 4. Performing Term Associations and Creating Word Clouds
6. Text Mining: 5. Hierarchical Clustering for Frequent Terms
7. Sochi #Olympics and #Crimea Tweets in R (and Justin Bieber?!)
8. Text Mining: 6. K-Medoids Clustering of #Ukraine Tweets in R
9. Text Mining: 7. Term Network Analysis Using #Ukraine Tweets in R
10. Text Mining: 8. #Ukraine Tweet Network Analysis in R
11. #PublicHealth on Twitter in R

Time Series Analysis:

1. Time Series: 1. Decomposition into Components-Additive Model
2. Time Series: 2. Forecasting Using Auto-Regressive Integrated Moving Averages (ARIMA)
3. World Wheat Production and Harvest Area, Part I
4. World Wheat Production Part II, Linear Filtering and Regression Forecasting
5. Up, Up, And Away: Amazon Stock Prices
6. How Fast is Fast? Comparing U.S. and South Korea Broadband Speeds
7. Visualizing Google Flu Trends in R
8. Visualizing Google Flu Trends Part 2
9. Ukraine Crisis and Palladium Prices
10. Visualizing CDC's Morbidity and Mortality Weekly Report (MMWR) on Infrequently Reported Diseases

Classification Analysis:

1. Decision Trees and Recursive Partitioning
2. Cluster Analysis: Using K-Means
3. Cluster Analysis: Choosing Optimal Cluster Number for K-Means Analysis
4. Cluster Analysis: Hierarchical Modeling
5. Creating Random Forests
6. Classifying Handwritten Digits (MNIST) using Random Forests

Regression Analysis:

1. Regression: Quantitative Structure-Activity Relationship (QSAR) Modeling
2. Robust Regression and Estimation of Model Performance
3. Partial Least Squares Regression, RMSEP, and Components
4. R: Comparing Multiple and Neural Network Regression
5. KDD Cup: Profit Optimization in R Part 1: Exploring Data
6. KDD Cup: Profit Optimization in R Part 2: Decision Trees
7. KDD Cup: Profit Optimization in R Part 3: Visualizing Results
8. KDD Cup: Profit Optimization in R Part 4: Selecting Trees
9. KDD Cup: Profit Optimization in R Part 5: Evaluation
10. Predicting Capital Bikeshare Demand in R: Part 1. Data Exploration
11. Predicting Capital Bikeshare Demand in R: Part 2. Regression
12. Predicting Capital Bikeshare Demand in R: Part 3. Generalized Boosted Model
Predicting Fraudulent Transactions is a series from Luis Torgo's  Data Mining with R book:
13. Predicting Fraudulent Transactions in R: Part 1. Transactions
14. Predicting Fraudulent Transactions in R: Part 2. Handling Missing Data
15. Predicting Fraudulent Transactions in R: Part 3. Handling Transaction Outliers
16Predicting Fraudulent Transactions in R: Part 4. Model Criterion, Precision & Recall
17. Predicting Fraudulent Transactions in R: Part 5. Normalized Distance to Typical Price

Neural Networks:

1. R: Neural Network Modeling Part 1
2. Neural Network Prediction of Handwritten Digits (MNIST) in R
3. R: Comparing Multiple and Neural Network Regression

Regular Expressions:

1. Using Regular Expressions to Analyze Baltimore Homicides in HTML, Part 1


1. R1.1: Probability Distributions - Random Sampling, Combinatorics
2. R1.2: Probability Distributions - Calculations for Statistical Distributions


1. RSA Encryption and Decryption


1. Why LeBron James Should Leave Miami: A Look At Win Shares

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