Page 89 - Demo

%u062c%u0645%u064a%u0639 %u0627%u0644%u062d%u0642%u0648%u0642 %u0645%u062d%u0641%u0648%u0638%u0629 %u0640 %u0627%u0625%u0644%u0639%u062a%u062f%u0627%u0621 %u0639%u0649%u0644 %u062d%u0642 %u0627%u0645%u0644%u0624%u0644%u0641 %u0628%u0627%u0644%u0646%u0633%u062e %u0623%u0648 %u0627%u0644%u0637%u0628%u0627%u0639%u0629 %u064a%u0639%u0631%u0636 %u0641%u0627%u0639%u0644%u0647 %u0644%u0644%u0645%u0633%u0627%u0626%u0644%u0629 %u0627%u0644%u0642%u0627%u0646%u0648%u0646%u064a%u062989a) learning step (model construction):- in this step describing a set of predetermined classes as each tuple/sample is assumed to belong to a predefined class, as determined by the class label attribute . the set of tuples used for model construction is training set .this model is represented as classification rules, decision trees, or mathematical formula b) classification step (model usage):- in this step classifying future or unknown objects , estimate accuracy of the model , the known label of test sample is compared with the classified result from the model . Accuracy rate is the percentage of test set samples that are correctly classified by the model.Test set is independent of training set (otherwise overfitting). If the test set is used to select models, it is called validation (test) set.