From the course: Text Analytics and Predictions with Python Essential Training
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Purpose - Python Tutorial
From the course: Text Analytics and Predictions with Python Essential Training
Purpose
- [Instructor] There may be times when you run into a really large dataset with different attributes and you need to find similarities. In this situation, you can use something called clustering which is a machine learning technique that helps group similar elements based on their attributes. Clustering is a great candidate to use unsupervised learning. In unsupervised learning, there is no training dataset with prior classification. Rather, the features of the elements are used to group similar elements into a single cluster organically. There are a number of techniques available like k-means clustering and k-nearest neighbors. With respect to text mining, how do you find features? The words in a document become the features. Documents with similar words get grouped together. Clustering algorithms use only numeric data so text data needs to be converted to numeric representations. Text frequency-inverse document frequency or TF-IDF is the most popular technique used for this purpose.…
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