Postgraduate Programmes - Loyal Academy

Classification is a predictive modeling problem that involves assigning a class label to each observation. Consequently, classification models generate a predicted class, which comes in the form of a discrete category; thus for most practical applications, a discrete category prediction is required in order to make a decision. However, this is highly influenced by class imbalances of data

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a. Explain what you understand by the term class imbalance b. Describe some consequences of using unbalanced classes in the classification c. Using appropriate examples, outline any two mechanisms of resolving the class imbalance problem d. Cite four different application areas in which class ...

MACHINE LEARNING, MASTER OF SCIENCE IN INFORMATION TECHNOLOGY, Postgraduate Programmes, UNIVERSITY 1 year 0 Answers 0 views Enlightened

Compare and contrast between each of the following pairs of machine learning models;

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a. Generative vs discriminative b. Parametric vs Non-parametric

MACHINE LEARNING, MASTER OF SCIENCE IN INFORMATION TECHNOLOGY, Postgraduate Programmes, UNIVERSITY 1 year 0 Answers 1 views Enlightened

Distance metrics play a significant role in neural network problems in determining the similarity and diversity of sample sets. Using appropriate examples, explain each of the following distance methods

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i. Euclidean Distance ii. Jaccard Index iii. Hamming Distance

MACHINE LEARNING, MASTER OF SCIENCE IN INFORMATION TECHNOLOGY, Postgraduate Programmes, UNIVERSITY 1 year 0 Answers 0 views Enlightened

Given the input vectors (1, 1, 1, 1) and (-1, 1, -1, -1) which are members of the class and target value 1; and the vectors (1, 1, 1, -1) and (1, -1, -1, 1) which are not members of the class hence target value of -1. Find the appropriate weights required to perform the classifications using an algorithm of your choice. Initialize the learning rate α to 1, and the weights to 0.

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MACHINE LEARNING, MASTER OF SCIENCE IN INFORMATION TECHNOLOGY, Postgraduate Programmes, UNIVERSITY 1 year 0 Answers 0 views Enlightened

Discuss the significance and applicability of the following theorems and method(s) as applied in Machine Learning;

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a. No Free Lunch (NFL) b. Ugly Duckling Theorem c. Bias-Variance Dilemma d. Jacknife and Bootstrap Methods

MACHINE LEARNING, MASTER OF SCIENCE IN INFORMATION TECHNOLOGY, Postgraduate Programmes, UNIVERSITY 1 year 0 Answers 1 views Enlightened

Using appropriate illustrations, discuss how each of the following tree classifiers are used in machine learning;

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a. Decision Trees b. Random Forests

MACHINE LEARNING, MASTER OF SCIENCE IN INFORMATION TECHNOLOGY, Postgraduate Programmes, UNIVERSITY 1 year 0 Answers 2 views Enlightened

The goal of machine learning to improve the performance P, on some task T over experience E. using these metrics (P, T, E). Using these metrics identify and justify any three application areas within which machine learning can be employed

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MACHINE LEARNING, MASTER OF SCIENCE IN INFORMATION TECHNOLOGY, Postgraduate Programmes, UNIVERSITY 1 year 0 Answers 0 views Enlightened

Machine learning is a branch of artificial intelligence that deals with the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. Explain three other domains that form part of machine learning

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MACHINE LEARNING, MASTER OF SCIENCE IN INFORMATION TECHNOLOGY, Postgraduate Programmes, UNIVERSITY 1 year 0 Answers 0 views Enlightened

Machine learning employs different strategies to enable a model to learn. Briefly explain each of the following strategies;

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a. Supervised Learning b. Unsupervised Learning c. Reinforcement Learning

MACHINE LEARNING, MASTER OF SCIENCE IN INFORMATION TECHNOLOGY, Postgraduate Programmes, UNIVERSITY 1 year 0 Answers 1 views Enlightened

If a graph is sparse which representation will you use and why?

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ADVANCED DATA STRUCTURES AND ALGORITHMS, MASTER OF SCIENCE IN DATA SCIENCE, Postgraduate Programmes, UNIVERSITY 1 year 0 Answers 2 views Enlightened

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