Machine Learning in R, in a nutshell
1035 Views
Josh Reich has created a concise R script demonstrating various machine-learning techniques in R with simple, self-contained examples. For example, here’s the code for K-means clustering:
k <- kmeans(train[,1:2],="">
plot(train[,1:2], type='n')
text(train[,1:2], as.character(k$cluster))
cm (train$class, k$cluster)
The techniques illustrated include:
- K-means clustering
- K nearest neighbours clustering
- Kernel clustering (via hand-rolled code)
- Recursive partitioning (regression trees)
- Principal Components Analysis (PCA)
- Linear Discriminant Analysis (LDA)
- Support Vector Machines (SVM)
While the code is concise, Josh also provides extensive comments explaining how the techniques work and are implemented in R. He’s also provided some slides to go with the script which go over the fundamentals of machine learning techniques. This is a great place to start if you’re thinking about doing some predictive analytics in R. (And don’t forget to check out the Machine Learning Task View on CRAN, too.)
i2pi: Machine Learning demo script and slides
Josh Reich has created a concise R script demonstrating various machine-learning techniques in R with simple, self-contained examples. For example, here’s the code for K-means clustering:
k <- kmeans(train[,1:2], 3)
plot(train[,1:2], type='n')
text(train[,1:2], as.character(k$cluster))
cm (train$class, k$cluster)
The techniques illustrated include:
- K-means clustering
- K nearest neighbours clustering
- Kernel clustering (via hand-rolled code)
- Recursive partitioning (regression trees)
- Principal Components Analysis (PCA)
- Linear Discriminant Analysis (LDA)
- Support Vector Machines (SVM)
While the code is concise, Josh also provides extensive comments explaining how the techniques work and are implemented in R. He’s also provided some slides to go with the script which go over the fundamentals of machine learning techniques. This is a great place to start if you’re thinking about doing some predictive analytics in R. (And don’t forget to check out the Machine Learning Task View on CRAN, too.)
i2pi: Machine Learning demo script and slides
Trending Now
1
Analytics
67 shares6,431 views
67 shares6,431 views
Deciphering Value Points Of Salesforce Einstein Analytics With Big Data
Arthur Koryaka - March 18, 20202
Big Data
47 shares4,586 views
47 shares4,586 views
The Growing Importance of Customer Data Mining for SMEs
Annie Qureshi - March 18, 2020
4
Big Data
31 shares4,273 views
31 shares4,273 views
6 Spectacular Reasons You Must Master the Data Sciences in 2020
Sean Mallon - March 17, 20205
Blockchain
61 shares4,316 views
61 shares4,316 views
Invest In The Right IoT Trend And Profit More In 2020
Olivia Taylor - March 17, 20206
Analytics
33 shares4,228 views
33 shares4,228 views
Data Analytics Provides New Insights on Email Marketing Metrics
Ryan Kh - March 17, 20207
Analytics
32 shares4,153 views
32 shares4,153 views
You must log in to post a comment.