Training a model is a key step in machine learning. Build a model for the exercise text data using the naive Bayes classifier.
- [Instructor] Now that our data is prepped, … we can move forward with building a classification model. … We need prior classifications … for the training data which is available … in the Course Classification.txt file. … We can load that file into the course_classes variable. … We can inspect the course_classes variable … to see its contents. … In order to actually go through the classification, … we need to split the data … into training and test datasets. … We will use the caret package for this. … Please install the caret package … if your setup does not have this. … I'm going to install the caret package now. … The package is successfully installed. … Let's load the caret package … through the library command. … We use the createDataPartition function … to split the data into training … and testing datasets. … Let's execute this code … and see how the train_set looks like. … It contains the indexes of the rows … that needs to go into the training dataset. … Rows that are not here, …
- 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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