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BIF601 Assignment 2 Solution and Discussion

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BIF601 GDB 1 Solutoion and Discussion

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@zareen said in BIF601 GDB 1 Solutoion and Discussion: Discuss different types of Machine Learning and Differentiate False +VE and False –VE, How they are significant? Solution Idea: In this section, we’ll define the primary building blocks of the metrics we’ll use to evaluate classification models. But first, a fable: An Aesop’s Fable: The Boy Who Cried Wolf (compressed) A shepherd boy gets bored tending the town’s flock. To have some fun, he cries out, “Wolf!” even though no wolf is in sight. The villagers run to protect the flock, but then get really mad when they realize the boy was playing a joke on them. [Iterate previous paragraph N times.] One night, the shepherd boy sees a real wolf approaching the flock and calls out, “Wolf!” The villagers refuse to be fooled again and stay in their houses. The hungry wolf turns the flock into lamb chops. The town goes hungry. Panic ensues. Let’s make the following definitions: “Wolf” is a positive class. “No wolf” is a negative class. We can summarize our “wolf-prediction” model using a 2x2 confusion matrix that depicts all four possible outcomes: True Positive (TP): False Positive (FP): Reality: A wolf threatened. Reality: No wolf threatened. Shepherd said: “Wolf.” Shepherd said: “Wolf.” Outcome: Shepherd is a hero. Outcome: Villagers are angry at shepherd for waking them up. False Negative (FN): True Negative (TN): Reality: A wolf threatened. Reality: No wolf threatened. Shepherd said: “No wolf.” Shepherd said: “No wolf.” Outcome: The wolf ate all the sheep. Outcome: Everyone is fine. A true positive is an outcome where the model correctly predicts the positive class. Similarly, a true negative is an outcome where the model correctly predicts the negative class. A false positive is an outcome where the model incorrectly predicts the positive class. And a false negative is an outcome where the model incorrectly predicts the negative class. In the following sections, we’ll look at how to evaluate classification models using metrics derived from these four outcomes. Source

BIF601 Assignment 1 Solution and Discussion

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Instructions:
Assignment No. 1 Bioinformatics Computing I (BIF601) FALL 2019
Make sure that you upload the solution file before due date. No assignment will be accepted through e-mail after the due date.
Formatting guidelines
 Use the font style “Times New Roman” and font size “12”.
 Compose your document in MS-Word, any file created in any format will not be accepted
and marked zero.
 Use black and blue font colors only.
Solution guidelines
 To solve this assignment, you should have good command over lectures 1-21.
 This is not a group assignment, it is an individual assignment so be careful and avoid
copying others‟ work
 Give the answer according to question only and avoid irrelevant details.
Please note that your assignment will not be graded if:
 It is submitted after due date
 The file you uploaded does not open
 The file you uploaded is copied from someone else
 It is in some format other than .doc
 Cheating or copying of assignment is strictly prohibited. The cheated or copied
assignment will be marked „Zero‟.
Total Marks: 20
Due date: 10-12-2019

WARNING

Plagiarism or hiring of ghost writers for solving the assignments will debar the student from award, if found at any stage.
All questions carry equal marks.
Question# 1: (6-Marks)
(a) Discuss Data Communication and component of a Data communication System? (b) How are computer communications used?
© What are the criteria‟s a Network must be able to meet?
Question# 2: (4-Marks)
a) Discuss the characteristics of LANs, MANs and WANs?
b) What are the advantages of using network and how LANs, WANs and MANs are
different?
Question# 3: (8-Marks)
Explain the following terms:

Topology and Star Topology - Bandwidth
Router
Wi-Fi
Question# 4: (2-Marks)
a) Write short note on OSI Model.
References:

Slides and handouts posted on the LMS
Textbook chapters as applicable
Recommended Books:
Data Communications and Networking 2nd Edition by Behrouz A. Forouzan
Data and Computer Communication 6th Edition by William Stallings