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About MACHINE LEARNING 1-5 (Ai &DS)
A feature vector in machine learning numerically represents an object by capturing its relevant characteristics as input for algorithms. Each element corresponds to a specific feature. Feature vectors enable algorithms to perform computations and predictions based on feature combinations. Feature spaces conceptually arrange data points based on their feature dimensions to reflect relationships patterns for analysis. Feature extraction transforms raw data into meaningful features to reduce complexity, while feature selection chooses only the most relevant features to enhance performance. Learning problem formulation defines the task by specifying the objective, data, features, labels, metrics, and algorithms to structure an effective solution.
Detailed Information
| Author: | ['Amani yar Khan'] |
|---|---|
| Publication Year: | 2023 |
| Pages: | 60 |
| Language: | English |
| Format: | |
| Price: | FREE |
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