Categorize the ML Problem: Analyze a Traffic Light image to find the signal (Red or Green or Amber)
A) Regression
B) Classification
C) Both
D) None of the above
The Correct Answer and Explanation is :
The correct answer is B) Classification.
Explanation:
In this problem, the goal is to analyze an image of a traffic light and determine which color the signal is—Red, Green, or Amber. This is a classic classification problem, where the task is to assign the input data (in this case, an image) to one of several predefined categories or classes.
Here’s why classification is the right choice:
- Definition of Classification: Classification is a supervised learning technique where the algorithm learns from labeled training data and makes predictions by categorizing new inputs into one of the predefined labels or classes. In this case, the labels are “Red,” “Green,” and “Amber.”
- Nature of the Output: The output in this problem is discrete, meaning it is one of a set number of possible options. The traffic light can only be one of three colors at a time, which aligns with the task of classification—selecting the correct category from a set of possible labels.
- Contrast with Regression: Regression is used when the output is continuous and can take on any numerical value. In this case, the task is not to predict a continuous value like temperature or height, but rather to identify which specific category (color) the traffic light belongs to. Therefore, regression would not be appropriate.
- Why Not Both?: Some problems may involve both classification and regression, but this is not one of them. The task is solely to determine which class (Red, Green, or Amber) the image belongs to, without any need for a continuous output.
In conclusion, this is a classification problem because the objective is to categorize the image into one of three discrete classes (colors of the traffic light).