Use k-means clustering to cluster elements based on their features. This will group similar elements together.
- [Narrator] Let's use clustering to group the courses … that we have already loaded. … We will use the k-means clustering function, … available in the standard stats package in R. … We first set the seed to 100, … so we can get the repeatable results … in the clustering process. … Let's try to create three clusters … from this group of courses. … We use the k-means function for the same. … We pass the documental matrix … and the number of clusters as parameters … for this function. … Next, we inspect the results … by looking at the cluster columns in the results. … It shows the cluster to which each of these … code's descriptions have been assigned. … Let's run the code … and review the results. … We then add this cluster information … to the original data frame, … so that we can look at the code's name … and the cluster side by side. … Finally, we sort … and print the results to show the code's descriptions … and their clusters. … Let's run the code now. … From the results, … we see that Java courses are generally …
- Creating a word cloud
- Analyzing sentiment
- Extracting emotions from text
- Clustering similar entities based on text
- Using classification for supervised learning
- Recommending items to users based on text data analytics
Skill Level Intermediate
Predictive Customer Analyticswith Kumaran Ponnambalam1h 37m Intermediate
1. Word Cloud
2. Sentiment Analysis
5. Predictive Text
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