supposefor exampleyou were given the following two sets of peoplea{abraham lincolngeorge washingtoncharles de gaulleb{benjamin harrisonjames madisonlouis napoleonnowsuppose that you were provided with the following partial descriptions of each of themabraham lincolnamericanpresident cm tall george washingtonamericanpresident cm tall benjamin harrisonamericanpresident cm tall james madisonamericanpresident cm tall louis napoleonfrenchpresident cm tall charles de gaullefrenchpresident cm tall based on this incomplete information about these historical figuresyou might infer that the process that assigned these examples to the set labeled or the set labeled involved separating tall presidents from shorter ones the incomplete information is typically called feature vector each element of the vector describes some aspect ( featureof the example there are large number of different approaches to machine learningbut all try to learn model that is generalization of the provided examples all have three componentsa representation of the modelan objective function for assessing the goodness of the modeland an optimization method for learning model that minimizes or maximizes the value of the objective function broadly speakingmachine learning algorithms can be thought of as either supervised or unsupervised in supervised learningwe start with set of feature vector/label pairs the goal is to derive from these examples rule that predicts the label associated with previously unseen feature vector for examplegiven the sets and ba learning algorithm might infer that all tall presidents should be labeled and all short presidents labeled when asked to assign label to thomas jeffersonamericanpresident cm it would then choose label supervised machine learning is broadly used in practice for such tasks as detecting fraudulent use of credit cards and recommending movies to people the best algorithms are quite sophisticatedand understanding them requires level of mathematical sophistication well beyond that assumed for this book consequentlywe will not cover them here much of the machine learning literature uses the word "classrather than "label since we use the word "classfor something else in this bookwe will stick to using "labelfor this concept