(2)Supervised Learning-1 ●Supervised Learning Task of inferring a function from labeled training data. The inferred function can be used for mapping new examples/unseen instances. Classical application: Regression of predicting numerical data; Classification of category labels; Predict sorting order. ·KNN,SVM DATA Copyright 2019 by Xiaoyu Li
Copyright © 2019 by Xiaoyu Li. 7 （2）Supervised Learning-1 Supervised Learning Task of inferring a function from labeled training data. The inferred function can be used for mapping new examples/ unseen instances. Classical application: Regression of predicting numerical data; Classification of category labels; Predict sorting order. KNN, SVM
(2)Supervised Learning-2 .Supervised Learning Process 1 Determine the type of training examples. .2 Gather a training set. 3 Determine the input feature representation of the learned function. .4 Determine the structure of the learned function and corresponding learning algorithm .5 Complete the design. 6 Evaluate the accuracy of the learned function. ATA 8 Copyright 2019 by Xiaoyu Li
Copyright © 2019 by Xiaoyu Li. 8 （2）Supervised Learning-2 Supervised Learning Process 1 Determine the type of training examples. 2 Gather a training set. 3 Determine the input feature representation of the learned function. 4 Determine the structure of the learned function and corresponding learning algorithm. 5 Complete the design. 6 Evaluate the accuracy of the learned function
(2)Supervised Learning-3 ●Supervised Learning YUPA DATA 9 Copyright 2019 by Xiaoyu Li
Copyright © 2019 by Xiaoyu Li. 9 （2）Supervised Learning-3 Supervised Learning
(3)Unsupervised Learning-1 Unsupervised Learning Trying to find hidden structure in unlabeled data. Clear or unclear task. No error or reward signal to evaluate a potential solution. ·Clustering .Anomaly detection 10 DATA Copyright 2019 by Xiaoyu Li
Copyright © 2019 by Xiaoyu Li. 10 （3）Unsupervised Learning-1 Unsupervised Learning Trying to find hidden structure in unlabeled data. Clear or unclear task. No error or reward signal to evaluate a potential solution. Clustering Anomaly detection
(3)Unsupervised Learning-2 Unsupervised Learning 11 DATA Copyright 2019 by Xiaoyu Li
Copyright © 2019 by Xiaoyu Li. 11 Unsupervised Learning （3）Unsupervised Learning-2