Q.No 10. Which of the following is false for the statement“perceptron learning algorithm,”a) Can only learn linearly separable problemsb) Updates its weights based on the sign of the errorc) Requires a pre-defined learning rated) Guarantees finding an optimal solution for any dataset

The behavior of a biological neural network can be captured by a simple model called an artificial neuron or perceptron. Which of the following statements about the perceptron is correct? a. Perceptrons can only be used for linearly separable problems. b. Perceptrons are a type of unsupervised learning algorithm. c. Perceptrons have no activation function. d. Perceptrons can have multiple layers, just like deep neural networks.

In the perceptron model, the weight ww vector is perpendicular to the linear decision boundary at all times. True False

What is the main function of a perceptron in an artificial neural network?<br /> A. 1. To compute a weighted sum of its inputs and apply an activation function to determine the output. <br />B. 2. To reduce the dimensionality of the inputs based on an activation function and learning rate. <br />C. 3. To cluster input data into positive and negative categories, followed by a sigmoid function. <br />D. 4. To optimize the network parameters using gradient descent and backward propagation.

Can a Perceptron be made to form non-linear decision boundary? (Choose the best answer)(1 點)

What is a perceptron?Select one:a.A type of machine learning algorithm for classification tasksb.A type of artificial neuron that can be trained to recognize patternsc.A type of deep learning neural networkd.A type of unsupervised learning algorithm