In Data mining, Classification is a process of finding a model that involves classifying the new observations based on observed patterns from the previous data. In short, if the target variable is discrete then it is a classification problem and if the target variable is continuous, it is a regression task.
The following are the most used classification algorithms in data mining:
- Logistic Regression
- Decision trees
- Random forest
- XG boost
Examples of classification in data mining include:
- Classification of emails as spam or not spam
- Classifying fraudulent and non-fraudulent transactions
If you wish to learn Data mining and predictive analytics using R, you can sign up for these Data Scientist by Intellipaat.
Also, watch this video on Data Mining:
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