Question

For the network above, We would like to classify nodes into 2 classes "+" and "-". Labels for node 3, 5, 8 and 10 are given (red for "+", blue for "-"). By using the following relational classifier: $$P(Y_i = c) = \frac{1}{|N_i|} \sum_{(i,j) \in E} W(i,j)P(Y_j = c)$$ Assuming all edge weights are equal to 1, an unbiased initialization of the unlabeled nodes, and an ordering according to the node ID, show the following (illustrating your steps): A. The probability distribution of the positive class over the unlabeled nodes at the second iteration of ICA B. Assuming at each step a threshold of 0.5 is used to determine whether the node is "+" or "-", show the final result of ICA algorithm and the class

Name: for the network above we would like to classify nodes into 2 classes and labels for node 3 5 8 and 10 are given red for blue for by using the following relational classifier pyi c frac1ni 25054
Uploaded: 2022-10-16T22:28:33-08:00
Duration: 48 s
Channel: Sri K
Description: for the network above we would like to classify nodes into 2 classes and labels for node 3 5 8 and 10 are given red for blue for by using the following relational classifier pyi c frac1ni 25054

          For the network above, We would like to classify nodes into 2 classes "+" and "-". Labels for node 3, 5, 8 and 10 are given (red for "+", blue for "-"). By using the following relational classifier:
$$P(Y_i = c) = \frac{1}{|N_i|} \sum_{(i,j) \in E} W(i,j)P(Y_j = c)$$
Assuming all edge weights are equal to 1, an unbiased initialization of the unlabeled nodes, and an ordering according to the node ID, show the following (illustrating your steps):
A. The probability distribution of the positive class over the unlabeled nodes at the second iteration of ICA
B. Assuming at each step a threshold of 0.5 is used to determine whether the node is "+" or "-", show the final result of ICA algorithm and the class

$for the network above we would like to classify nodes into 2 classes and labels for node 3 5 8 and 10 are given red for blue for by using the following relational classifier pyi c frac1ni 25054$

Added by Marissa J.

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