if there is only a discrete number of possible outcomes (called categories), the process becomes a .

Related MCQs

• if there is only a discrete number of possible outcomes (called categories), the process becomes a           .
• if there is only a discrete number of possible outcomes (called categories), the process becomes a            .
• if there is only a discrete number of possible outcomes (called categories), the process becomes a______.
• If there is only a discrete number of possible outcomes called          .
• If there is only a discrete number of possible outcomes called _____.
• A machine learning problem involves four attributes plus a class. The attributes have 3, 2, 2, and 2 possible values each. The class has 3 possible values. How many maximum possible different examples are there?
• We can also compute the coefficient of linear regression with the help of an analytical method called Normal Equation. Which of the following is/are true about Normal Equation? 1. We don't have to choose the learning rate 2. It becomes slow when number of features is very large 3. No need to iterate
• We can also compute the coefficient of linear regression with the help of an analytical method called �Normal Equation�. Which of the following is/are true about �Normal Equation�?1. We don�t have to choose the learning rate2. It becomes slow when number of features is very large3. No need to iterate
• We can also compute the coefficient of linear regression with the help of an analytical method called “Normal Equation”. Which of the following is/are true about “Normal Equation”? 1. We don’t have to choose the learning rate 2. It becomes slow when number of features is very large 3. No need to iterate
• We can also compute the coefficient of linear regression with the help of an analytical method called “Normal Equation”. Which of the following is/are true about “Normal Equation”?1. We don’t have to choose the learning rate2. It becomes slow when number of features is very large3. No need to iterate