Consider the above dataset consisting of 3 binary attributes ("attr1', 'attr2', 'attr3') and one binary 'class'. There are 14 total training instances. The goal is to build a decision tree using the ID3 algorithm. Starting with the entire dataset and following the algorithm discussed in the class, provide the information gain values for all the four attributes. Provide answers rounded to 4 numbers after the decimal point (e.g., if the calculated value is either 0.1, 0.11114, 0.11115, you must provide 0.1000, 0.1111, 0.1112 as the answer respectively) Information Gain for 'attr1' attribute - Information Gain for 'attr2' attribute - Information Gain for 'attr3' attribute -