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An artificial neural network (ANN) is a computational model inspired by the structure and functioning of the human brain. It is a key component of machine learning and data mining, often used for tasks such as classification, regression, pattern recognition, and decision-making. Neural networks consist of interconnected nodes, called neurons, organized into layers. The layers typically include an input layer, one or more hidden layers, and an output layer.
Here are key components and concepts associated with artificial neural networks in data mining:
Neurons and Layers:
Weights and Biases:
Activation Function:
Feedforward and Backpropagation:
Training:
Types of Neural Networks:
Applications in Data Mining:
Challenges and Considerations:
Artificial neural networks have proven to be powerful tools in data mining and machine learning, demonstrating their ability to model complex relationships and patterns in diverse datasets. Advances in neural network architectures and training algorithms have contributed to their widespread adoption in various industries and applications.
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