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] Not to be confused with clustering, classification is another use case for text mining. Classification is a machine learning technique for supervised learning. Recall that clustering is used with unsupervised learning. Its goal is to create classes of entities and then build a model to identify the class of a specific entity. Classification algorithms build models based on a target variable in the dataset. It uses other feature variables available in the dataset to build these models. The model so built is used to predict the class of new data. It predicts the target variable based on other feature variables available in the new data. We split the source data into training data and test data. Training data is used to build the model and test data is used to test its accuracy. How do we do classification for text mining? In text mining, words in a document become feature variables. For the purpose of training models each document needs to be tagged with the specific…
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