Lec 4 | Learning

Question 1

It provides a computer with data, rather than explicit instructions. Using these data, the computer learns to recognize patterns and becomes able to execute tasks on its own.

Answer 1

Machine Learning

Question 2

It is a task where a computer learns a function that maps inputs to outputs based on a dataset of input-output pairs.

Answer 2

Supervised Learning

Question 3

This is a supervised learning task where the function maps an input to a discrete output. In other terms, it is the task learning a function mapping an input point to a discrete category.

Answer 3

Classification

Question 4

• An algorithm, given an input,chooses the class of the nearest data point to that input.
• One way of solving a task by assigning the variable in question the value of the closest observation

Answer 4

Nearest-Neighbor Classification

Question 5

An algorithm that, given an input, chooses the most common class out of the k nearest data points to that input

Answer 5

k-nearest-neighbor classification

Question 6

What is a drawback of using k-nearest-neighbor classification?

Answer 6

A drawback is that, using a naive approach, the algorithm will have to measure the distance of every single point to the point in question, which is computationally expensive. This can be sped up by using data structures that enable finding neighbors more quickly or by pruning irrelevant observation.

Question 7

Another way of going about a calssification problemis looking at the data as a whole and trying to create a decision boundary. In two-dimensional data, we can draw a line between the two types of observations. Every additional data point will be classified based on the side of the line on which it is plotted.

Answer 7

Perceptron Learning

Question 8

What is the perceptron learning rule?

Answer 8

Given data point (x, y), update each weight according to:
wi = wi + α(y - hw(x)) × xi

or

wi = wi + α(actual value - estimate) × xi