Independent Cascade Model and Linear Threshold Model in information spread

Q: give an example of a misleading pie chart and bar graph. explain why they are misleading

A: give an example of a misleading pie chart and bar graph. explain why they are misleading.

Q: Consider Diffie-Hellman protocol. What is the Diffie-Hellman protocol used for? Given p = 13, g = 4,…

A: Answer first:

Q: If a set of WFFS has no truth-value assig

A: We need to Solve the 2 given question.

Q: Define simple exponential smoothing?

A: Exponential smoothing can be categorize with many types like single, double, triple etc..

Q: A high bias model has a high unpredictable error, while a high variance model has a high systematic…

A: Defined the given statement as true or false

Q: p) Based on the information that you can observed from Figure 3(i) and 3(ii), if you are required to…

A: Below i have explained:

Q: defined a proper policy for an MDP as one that is guaranteed to reach a terminal state. Show that it…

A:

Q: What exactly is meant by the term "bridge/junction table? What other options are there than this…

A: According to the provided information, we must define the bridge table, its alternative, and its…

Q: The relationship between BQP and NP is unclear.

A: Introduction: Bounded-Error Quantum Polynomial-Time is the abbreviation for Class BQP. They are the…

Q: Define the following terms related to parallelism and dependence relations: (a) Computational…

A: Parallelism : When two process runs simultaneously within the CPU then this condition is known as…

Q: The importance of the hidden Markov chain in a historical data set should be discussed.

A: Given To discuss to hidden Markov chain in a historical data set

Q: Both the Classical Waterfall model and the Rational Unified model will be evaluated in this…

A: First of all, The waterfall model is working on a sequential model hence the software development…

Q: In a historical dataset, discuss the importance of a hidden markov chain.

A: Introduction: The relevance of the hidden Markov chain in a historical data set

Q: What is a perceptron network model? How could such a model be used to perform simple linear…

A: The answer is

Q: Question 3 Construct a labeled diagram of Multilayer Perception Network (ANN-MLP) with one hidden…

A: Consider the neural networ which contains :- three inputs  one hidden layer two output

Q: Avoid plagiarism by writing 300-500 words per conversation. What role does the concealed markov…

A: INTRODUCTION: Here we need to tell the role of markov chain in historical data.

Q: gives

A: Introduction:   Petri net:   A Petri net is a graphical mathematics modeling tool used to…

Q: Consider data with two Boolean attributes A and B. A B Label count of examples 50 1 50 1 1 100 What…

A: The contingency table after splitting on attributes A and B are :   A=1 A=0 + 1 0 - 1 2…

Q: With the help of Moores Law explains why it is significant in the development of ERP. Is Moores Law…

A: Moore's law : The number of transistors per square inch on integrated circuits had doubled every…

Q: Question 4: There are different empirical loss prediction models you have studied. Explain…

A: Empirical models Empirical models are only supported by experimental data. The fundamentals and…

Q: compare the utility of a data model to the classic strength prediction technique

A: Introduction: To address the issue, we must discuss the use of a data model in the context of the…

Q: Name any three SDLC models,Briefely explain Water fall model with diagram.

A: SDLC Methodology: SDLC stands for Systems Development Life Cycle. It is a formalized, standard and…

Q: How many states have a nonsimplified Markov chain for a system consisting of n components? Assume…

A: Answer : It is given in question that  system consisting n components and each components has two…

Q: Give a definition for the word 'Amortized Analysis.

A: Amortized analysis is used for analyze the algorithms.  This amortized analysis is used when the…

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A: NOTE  :-  Below i explain the answer in my own words by which you understand it well.   The…

Q: Explain collision & abortion in CSMA/CD with neat diagram and also explain flow diagram for CSMA/CD.

A:

Q: Classify above discrete-time system it terms of: a. Causality b. Memory System c. Linearity d.…

A: a. Causality:

Q: What is the accuracy of always-taken and always-not-taken predictors for this sequence of branch…

A: Accuracy of always-taken predicators: Always Taken Predictors for this sequence of these outcomes…

Q: Moores Law is used to build ERP. Exists Moore's Law today?

A: Moore's Law: Ever since integrated circuits were invented, the number of transistors per square…

Q: In the network model, the one to many relationship is denoted by

A: the one to many relationship is denoted by

Q: If the sum of the index values in the sequence model is 28, what is the TMU and its time equivalent…

A: Answer is in next step

Q: hidden markov chain's historical significance.

A: Why is hidden Markov important?   A hidden Markov model (HMM) is a statistical model that can be…

Q: defined a proper policy for an MDP as one that is guaranteed to reach a terminal state. Show that it…

A: In Machine learning the Reinforcement learning (RL) which refers to the an area of the machine…

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A:

Q: Consider the growing network sequence shown in Figure Q-3.1. Is this network sequence fractal? Why…

A: Given: Consider the growing network sequence shown in Figure Q-3.1.(a)  Is this network sequence…

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A: DES exhibits avalanche: The protection technique that does not give the analog voltage will result…

Q: Question 9) Consider the following transition diagram and state whether the CTL formula AFAG p and…

A: Below i have answered:

Q: Why are too many features a problem for k-NN classification but not for Naive Bayes classification?

A: Given: Why is there an issue with too many features in k-NN classification but not in Naive Bayes…

Q: Model which combines elements of waterfall model applied in an iterative fashion is a. RAD model b.…

A: Model which combines elements of waterfall model applied in an iterative fashion is a. RAD model…

Q: Discuss the historical importance of the concealed markov chain.

A: Markov Chains are extremely useful for modelling discrete-time, discrete-space stochastic processes…

Q: Given the following sequence of transitions, define the transition function for each derivation.…

A:

Q: scuss the significance of hidden markov chain in a historic

A: significance of hidden markov chain in a historic data

Q: Question no. 1: design Schematic diagram and verify truth table. Of given ci ABC Out 000 |0 001 0…

A: A truth table is a chart of 1s and 0s arranged to indicate the results (or outputs) of all possible…

Q: Calculate time complexity using amortized analysis

A: Amortized analysis: Amortized Analysis is utilized in algorithms when one operation is relatively…

Time Complexity

In computer science, the computational complexity that is measured in terms of time is referred to as time complexity that defines how long it takes a computer to execute an algorithm. An algorithm's time complexity is measured by the the amount of time required to execute each statement of code in the algorithm. If a statement is set to execute repetitively, the number of times it will be N multiplied by the time it takes to run that function each time is equal .