149 views

1 Answer

0 0 votes
We would have the joint distribution:

$$
P\left(X_1, X_2, X_3, X_4, Y\right)
$$

where $X_1, X_2, X_3, X_4$ are the attributes and $Y$ is the class label. The total number of entries in this table would be:

$$
3^4 \times 2=162 \text { entries }
$$

Since probabilities must sum to 1 , the number of independent parameters is:

$$
3^4 \times 2-1=161 \text { independent parameters. }
$$
 
Answer:
Position:
Show:

Related questions

0 0 votes
1 1 answer
167
167 views
GO Classes asked Mar 19, 2025
167 views
Consider a naive Bayes classifier with 3 boolean input variables, $X_1, X_2$ and $X_3$, and one boolean output, $Y$.How many parameters must be estimated to train such a ...
0 0 votes
1 1 answer
128
128 views
GO Classes asked Mar 19, 2025
128 views
Suppose you have the following training set with three boolean input $x, y$ and $z$, and a boolean output $U$.\begin{array}{|c|c|c|c|}\hline x & y & z & U \\\hline \hline...
0 0 votes
1 1 answer
156
156 views
GO Classes asked Mar 19, 2025
156 views
\begin{array}{|c|c|c|}\hline A_1 & A_2 & \text { Class Label } Y \\\hline \text { True } & \text { True } & + \\\hline \text { True } & \text { True } & + \\\hline \text ...
0 0 votes
1 1 answer
155
155 views
GO Classes asked Mar 19, 2025
155 views
Suppose we are given the following dataset, where $A, B, C$ are input binary random variables, and $y$ is a binary output whose value we want to predict.\begin{array}{|c|...