4. We are going to consider the example from Tom Mitchell book to understand Candidate Elimination. Consider the example task of learning the target concept "days on which my friend Aldo enjoys his favorite water sport. Table below describes a set of example days, each represented by a set of attributes. The attribute EnjoySport indicates whether or not Aldo enjoys his favorite water sport on this day and is the class label that we will try to predict The task is to learn to predict the value of EnjoySport for an arbitrary day, based on the values of its other attributes Let each input example be a vector of following six attributes . Sky (with possible values Sunny, Cloudy, and Rainy) AirTemp (with values Warm and Cold) Humidity (with values Normal and High) . Wind (with values Strong and Weak) . Water (with values Warm and Cool) Forecast (with values Same and Change) Using the Candidate Elimination algorithm discussed in the class, find the correct answer below. The training data is shown below Example Sky AirTemp Humidity Wind Water Forecast EnjoySport Sunny Warm High Strong Cool Change Yes Sunny Warm Normal Strong Warm Same Yes Rainy Cold High Strong Warm Same No Sunny Warm High Strong Warm Same Yes O a) After observing all four training examples, the total number of hypotheses in the version space is 6 c) After observing all four training examples, the total number of d) If the fifth training example is O b) Hypothesis ?,7,7,Strong,?,?) is part of the version space O hypotheses in the general and specific boundaries is 4 O Rainy, Warm, High, Strong, Cool, Change), No None of the boundaries (S or G) are modified. 4. We are going to consider the example from Tom Mitchell book to understand Candidate Elimination. Consider the example task of learning the target concept "days on which my friend Aldo enjoys his favorite water sport. Table below describes a set of example days, each represented by a set of attributes. The attribute EnjoySport indicates whether or not Aldo enjoys his favorite water sport on this day and is the class label that we will try to predict The task is to learn to predict the value of EnjoySport for an arbitrary day, based on the values of its other attributes Let each input example be a vector of following six attributes . Sky (with possible values Sunny, Cloudy, and Rainy) AirTemp (with values Warm and Cold) Humidity (with values Normal and High) . Wind (with values Strong and Weak) . Water (with values Warm and Cool) Forecast (with values Same and Change) Using the Candidate Elimination algorithm discussed in the class, find the correct answer below. The training data is shown below Example Sky AirTemp Humidity Wind Water Forecast EnjoySport Sunny Warm High Strong Cool Change Yes Sunny Warm Normal Strong Warm Same Yes Rainy Cold High Strong Warm Same No Sunny Warm High Strong Warm Same Yes O a) After observing all four training examples, the total number of hypotheses in the version space is 6 c) After observing all four training examples, the total number of d) If the fifth training example is O b) Hypothesis ?,7,7,Strong,?,?) is part of the version space O hypotheses in the general and specific boundaries is 4 O Rainy, Warm, High, Strong, Cool, Change), No None of the boundaries (S or G) are modified
