R Classification & Clustering
RStudio 1.1.4
| Intermediate
- 8 Videos | 38m 42s
- Includes Assessment
- Earns a Badge
Explore the advantages of the programming language R in this 8-video Skillsoft Aspire course. An essential skill for statistical computing and graphics, R is the tool of choice for data science professionals in every industry and field. It both creates reproducible high-quality analyses, and offers unparalleled graphic and charting capabilities. Learners will examine how to apply classification and clustering methods to data science problems by using R. Key concepts covered in this course include performing the preparatory steps needed to create a classification and decision tree; using the rpart library and ctree library to build a decision tree; and how to perform the preparatory steps needed to carry out clustering. Next, explore use of the k-means clustering method; using hierarchical clustering with the hclust and cutree methods; and applying a decision tree method to a classification problem. Finally, learn to train a decision tree classifier by using the data and a relationship inside of those data.
WHAT YOU WILL LEARN
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perform the preparatory steps needed to create a classification and decision treeuse the rpart library to build a decision treeuse the ctree library to build a decision treeperform the preparatory steps needed to carry out clustering
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use the k-means clustering methoduse hierarchical clustering with the hclust and cutree methodsapply a decision tree method to a classification problem
IN THIS COURSE
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1.Course Overview1m 34sUP NEXT
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2.Preparing Data for Classification6m 28s
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3.Using rpart5m 34s
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4.Using ctree6m 10s
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5.Preparing Data for Clustering4m 4s
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6.Using K-Means Clustering3m 49s
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7.Using Hierarchical Clustering5m 20s
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8.Exercise: Creating a Decision Tree5m 43s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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