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- Consider the decision model/game theoretic model from Chapter 19 for the spread of a new behavior through a social network. Suppose we have the social network depicted in Figure 2; suppose that each node starts with the behavior B, and each node has a threshold of q = 2/5 for switching to behavior A. Now, let c and d form a two-node set S of initial adopters of behavior A. If other nodes follow the threshold rule for choosing behaviors, which nodes will eventually switch to A? Give a brief (1-2 sentence) explanation for your answer. Find a cluster of density greater than 1 − q = 3/5 in the part of the graph outside S that blocks behavior A from spreading to all nodes, starting from S, at threshold q. Give a brief (1-2 sentence) explanation for your answer. Suppose you were allowed to add a single edge to the given network, connecting one of nodes c or d to any one node that it is not currently connected to. Could you do this in such a way that now behavior A, starting from S and…Here, you may choose from two different theories: the Path-Goal Theory and the Leader-Member Exchange (LMX) Theory. Real-world examples are useful for making any point more understandable.The accuracy in the output depends on the correct inputs. The model designed is supposedto be evaluated to determine the accuracy and it is supposed to function in a supervisedway. Hence the data sets can affect the model and vice versa.Given P(D|M) ,P(M) ,and P(D'|M), solve the followinga)Draw the probability tree for the main situationB)Draw the reverse tree for the main situation.C)Using the main tree, prove all probabilities on the opposite tree.D) If P(DIM) = 0.3,P(M) = 0.1 ,and P(D'IM) = 0.65 find P(D)
- Draw a decision tree. Determine the expected value for each decision and event nodes. Which alternative is the best for the businessman?Make a Venn diagram showing the relationships among test cases from boundary value analysis, robustness testing, worst-case testing, and robust worst-case testing.Create a decision tree from the data below where the final classes are a binary response to the class identifier "preferred". To decide on the splits for the tree, use Gini to determine the gain ratio, and take the split that offers the highest gain ratio.
- In this situation, you can think about both the Path-Goal Theory and the Leader-Member Exchange (LMX) Theory. Use examples from real life to make your answer clearer and more convincing.1. In decision-making under risk, does states of nature represents the events in a chance node? Briefly explainJust how can one arrive at a conclusion as to which model is optimal for the system?
- Consider the Path-Goal Theory and the Leader-Member Exchange (LMX) Theory. Use real-life examples to clarify and persuade.Note: select one of the problems you prefer, and please send me all the detail after finishing it With this assignment, you’ll implement one of the problems listed below. JADE agents also.- Ant-based clustering- Fire escape scenario - Prey-predator - Covid pandemic- Motion of fluids or gases- Or Any other brilliant idea best fits with agent-based phenomenaProbability distributions (Normal, Uniform, Exponential and etc.) for Interarrival times and processing times can be calculated by third-party Java libraries such as Apache Commons.Logging created random numbers by Java and verifying them with Excel, Arena Input Analyzer or sth else will be a part of this step. Data Exchange between agents may be handled by ACLMessages. 1) Designing and implementing a working FIPA-compliant agent-based simulation system Your code must include; - Inline agent creation- Several behaviors of different kinds (Ticker, Waker, and etc.)- Messaging (send and receive)- Agent type definition and searching by…Develop a CART model using the test data set that utilizes the same target and predictor variables. Visualize the decision tree. Compare the decision trees. Does the test data result match the training data result?