Types of classification problems
- Binary Classification:
- Involves two classes.
- Example: Spam vs. Not Spam in email filtering.
- Multiclass Classification:
- Involves more than two classes.
- Example: Handwriting recognition for digits 0-9.
- Multilabel Classification:
- Each instance can belong to multiple classes simultaneously.
- Example: Tagging a news article with multiple categories like “Politics”, “Economy”, “Health”.
- Image Classification:
- Involves classifying images into different categories.
- Example: Identifying objects in images, such as dogs, cats, cars, etc.
- Text Classification:
- Involves categorizing text into predefined classes.
- Example: Sentiment analysis on customer reviews (Positive, Negative, Neutral).
- Time-Series Classification:
- Instances are ordered sequences, and the goal is to classify entire sequences.
- Example: Activity recognition from wearable sensor data over time.
Typical models