If the input vectors arand initial values of three weight vectors are
then calculate the resulting weight found after training the competitive layer with Kohonen’s rule and a learning rate
of 0.5 on the input-series in order I1,I2,and I3,
We are given: Inputs: $$ I_1 = \begin{bmatrix} -1 \\ 0 \end{bmatrix}, \quad I_2 = \begin{bmatrix} 0 \\ 1 \end{bmatrix}, \quad I_3 = \begin{bmatrix} \sqrt{2} \\ \frac{1}{\sqrt{2}} \end{bmatrix} $$ Initial weights ____ _____ _________ ______ __________ ____ ___ _________ _____ _________ _________ _________.
______ __________ _____ ____ _____ _______ ______ ______ _______.
___ __________ __________ ________ ____ _______ ________ ________ ___ ______ _______.
_____ ___ ______ _______ _________ _____ ______ _______ _____ _________.
_________ ________ ___ _______ _________ _____ _________ ________ _________ ___ _____ ____.
______ ______ ________ __________ _________ ____ ____ _______ _________ _______ _______ ________.
_________ __________ _________ ______ ______ ________ ____ ___ ________ ____ _____ _____.
_____ _____ _______ ___ ________ __________.
_____ __________ ______ _____ ____ _______ __________ _____ __________.
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Unsupervised learning,
Supervised Learning,
Semi-supervised.
What is the role of loss function in machine learning algorithms? Explain any two commonly used loss functions in machine learning algorithms.
Consider the following table for the connections between the input neurons and the hidden layer neurons.
| Input neuron | Hidden layer neurons | Connection weithts |
| 1 | 1 | 1 |
| 1 | 2 | 0.1 |
| 1 | 3 | -1 |
| 2 | 1 | 1 |
| 2 | 2 | -1 |
| 2 | 3 | -1 |
| 3 | 1 | 0.2 |
| 3 | 2 | 0.3 |
| 3 | 3 | 0.6 |
Reinforcement Learning,
If the input vectors arand initial values of three weight vectors are
then calculate the resulting weight found after training the competitive layer with Kohonen’s rule and a learning rate
of 0.5 on the input-series in order I1,I2,and I3,