Course: Soft Computing (TA)

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Across
  1. 5. one of the basic units of a neural network that mimics a biological neuron
  2. 6. Adaptive Linear Neural Element network
  3. 7. A computing paradigm that deals with imprecision and approximation rather than exact solutions
  4. 11. A method of learning where the model finds patterns in data without labeled outputs
  5. 13. The threshold-based function that decides the output of a perceptron
  6. 14. A technique used in machine learning where labeled data is used to train a model
  7. 15. A perceptron variant that is capable of solving non-linearly separable problems
Down
  1. 1. The training process in a neural network where errors are propagated backward to adjust weights
  2. 2. The process of improving a model's accuracy by minimizing the difference between predicted and actual values
  3. 3. The interconnected processing elements in an artificial neural network are known as:
  4. 4. The kind of neural network where signals only move in one direction, from input to output
  5. 8. An automated vehicle refers to an application of
  6. 9. Negative sign of weight indicates___ input
  7. 10. Each connection link in ANN is linked with ___
  8. 12. In adaline model what is the relation between output & activation value(x)