Data Mining Methods(1)

 Bilal Hussain Malik

21/3/25 

                                                          Data Mining Methods

                                                         Classification

Classification is a supervised learning method that categorizes data into known categories. Using algorithms like decision trees, SVM, or neural networks, it is trained using labeled training data to predict class labels for novel cases. Common applications include spam filtering (spam or ham labeling of emails), medical diagnosis (disease diagnosis from symptoms), and credit card fraud detection. It involves feature selection, model training, and validation in order to get accuracy. Some of the greatest challenges include handling unbalanced data and overfitting. Performance is measured in terms of precision, recall, and F1-score. Classification is best when there are clear categories and there is a sufficient amount of tagged data, making it central in pattern recognition and forecast analysis in business.