Financial Risk Manager Part 1
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Which of the following best describes a neural network as a technique for machine learning?
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TTanishq
A
A neural network is a precise replica of the human nervous system
B
A neural network is based on various linear regression models
C
A neural network is made up of interconnected nodes and links, and it is particularly effective at modeling non-linear relationships between the input data
D
A neural network is structured like a tree, with nodes representing the features and the relationships between them being linear
Explanation:
Explanation
Option C is correct because:
- Neural networks consist of interconnected nodes (neurons) organized in layers (input, hidden, output)
- The connections between nodes have weights that are adjusted during training
- They are particularly effective at modeling complex non-linear relationships due to their ability to learn hierarchical representations of data
- The activation functions in neurons (like sigmoid, ReLU, tanh) introduce non-linearity, enabling the network to approximate complex functions
Why other options are incorrect:
- Option A: Neural networks are inspired by biological neural networks but are not precise replicas of the human nervous system
- Option B: While neural networks can perform regression, they are not based on linear regression models - they can model non-linear relationships
- Option D: This describes a decision tree structure, not a neural network. Neural networks have layered architectures, not tree-like structures
Neural networks excel at pattern recognition, classification, and regression tasks where the relationships between variables are complex and non-linear.
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