Rangkuman Classification is a form of data analysis that extracts models describing important data classes.
{"Image DocumentName": "Rangkuman Classification is a form of data analysis that extracts models describing important data classes.", "Image ImageDescription": "Effective and scalable methods have been developed for decision tree induction, Naive Bayesian classification, rule-based classification, and many other classification methods. Evaluation metrics include: accuracy, sensitivity, specificity, precision, recall, F measure, and F\u00df measure. Stratified k-fold cross-validation is recommended for accuracy estimation. Bagging and boosting can be used to increase overall accuracy by learning and combining a series of individual models.", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}