You must predict next month's sales as a number. Which technique fits?
Why C is the answer
Regression
Regression predicts a numeric value.
In detail
- Predicting a number is regression.
- A numeric target points to regression.
Use case
An illustrative scenario, not a real incident.
A store predicts next month's revenue as an amount, so regression fits.
See it in different ways
flowchart TD
A{"What does the data look like?"} -->|"Labeled examples"| B["Supervised: classification, regression"]
A -->|"No labels"| C["Unsupervised: clustering"]
A -->|"Rewards from actions"| D["Reinforcement learning"]mindmap
root((Machine learning))
Supervised
Regression: a number
Classification: a label
Unsupervised
Clustering
Reinforcement
Learns from rewardsflowchart TD
Q{"What do you predict?"}
Q -->|"A number"| A0["Regression"]
Q -->|"A category"| A1["Classification"]Key point: Regression predicts numbers.
Why the other options are wrong
- A. Dimensionality reduction
- That reduces features.
- B. Clustering
- Clustering finds groups.
- D. Binary classification
- Classification predicts a label.