Use the model to predict classes for new data and test its accuracy.
- [Instructor] In this video, … we will predict the class of the course descriptions … based on the classifier we have built. … We will predict for the test dataset we created … in the previous video. … We do so using the predict function … and generate the results in the course_predictions variable. … The predict function takes as input … the model that we have built … and the test data that needs to be used for predictions. … The actual predictions for the test data are returned … by this function. … We can then use the confusion_matrix function … to measure the accuracy of the model built. … Confusion_matrix compares the predictions … with the actual classifications for the text data. … Let's run the code and review the results. … The overall accuracy of this model stands at 75%. … If we repeat the model with a different set … of training and test datasets, … you may get different results. … Given that we used very few samples … and very few test sets, … the result may vary widely. …
- 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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