EXAMPLE 2.5 In Section 2.1.1, we noted that there can be many relations on a given set, and we mentioned several for the attribute height. The representa- tion condition has implications for each of these relations. Consider these examples: For the (binary) empirical relation taller than, we can have the numerical relation x> y Then, the representation condition requires that for A taller than B if and only if M(A) > M(B) For the (unary) empirical relation is-tall, we might have the numerical relation 36 Software Metrics any measure M, X>70 The representation condition requires that for any measure M, A is-tall if and only if M(A) > 70 For the (binary) empirical relation much taller than, we might have the numerical relation x>y+15 The representation condition requires that for any measure M, A much taller than B if and only if M(A) > M(B) + 15 For the (ternary) empirical relation x higher than y if sitting on z's shoulders, we could have the numerical relation 0.7x + 0.8z>y The representation condition requires that for any measure M,

The class I'm taking is computer science discrete structures. I am completely stuck. Please help! If you can please add an explanation with answer so I can better understand . Thank you!

When the issue set contains only nominal characteristics, vector space-based classification algorithms are usually not the best solution. What are your thoughts on this statement? How would you utilise machine learning to categorise nominal data?

The USES relation naturally forms a graph. As mentioned in the lecture, the USES relation graph should be a Directed Acyclic Graph (DAG). (1) A graph could be represented with two different data structures, i.e., adjacency list and adjacency matrix. Represent the USES relation graph in Figure 3-1 with adjacency list and adjacency matrix. 3 2 4 5 6. Figure 3-1: USES relation graph of the modules in a system (2) Suppose the input of a USES relation graph is represented with adjacency list, develop a function in pseudocode to check whether the USES relation graph is an acyclic graph, using Stepwise Refinement technique taught in lectures. You should provide with at least 2 refinements. Assuming there are V vertices and E edges, please state the time complexity of your algorithm.