Assignment 2: Regression vs Classification.

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Posted on January 22, 2025
Assignment 2: Regression vs Classification.
Read Chapter 3: Regression from "Gulli, A., Kapoor, A., Pal, S. (2019).  Deep Learning with TensorFlow 2 and Keras: Regression Deep Learning with TensorFlow 2 and Keras: Regression - Alternative Formats , ConvNets, GANs, RNNs, NLP, and More with TensorFlow 2 and the Keras API, 2nd Edition. United Kingdom: Packt Publishing." Then, create your own examples to explain the difference between regression and classification. You can use the source code for Chapter 3.
For the submission provide a plain text that shows:
  1. creation of real number example for regression problem
  2. creation real number example for classification problem
  3. explanation of differences in calculations and meaning between regression and classification
Make sure that the 'SafeAssign' score is lower than 30%.

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Solution

Finding a mathematical correlation (regression model) between the number of years of experience and the wage is the goal of the regression problem. The target variable (salary) is a continuous real value, and the objective is to forecast an individual's precise compensation depending on their experience level. The dataset-based model aims to estimate the wage as a function of years of experience, enabling you to anticipate salaries for people with various degrees of expertise.

In the table above , the "Classification" column represents the class labels, where 1.0 is used to represent "Pass," and 0.0 is used to represent "Fail." This is a way to simulate a classification problem with real numbers, but it's important to note that real number classification problems are not common in practice. Typically, classification problems involve discrete categories or labels.

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