I am working on a MATLAB code for cross validation.
I have define the test and training set but I am having trouble using the anfis command. Before carrying out the training using anfis command I need to define the fismat. How do i define fismat?
My code is as follows:
load visit1.mat...
IM given a question on MATLAB programming.
It ask to construct a numerical generative model for autoregressive model of order two;
xt -xt-1 + 0.5t-2 = et. generate and plot 256 time series samples.
then numerically obtain the spectrum of this time series and plot them.
assuming noise process...
Hi
I am doing this exercise (2 class problem with 2-dimensional features) and I have solved the linear discriminant function which turns out be y1(x) - y2(x) = 2x1 +2x2
I am having difficulty in finding the class posterior probabilities frm the linear discriminant function obtained...
So the Bayesian approach was right. I taught I was wrong at the first place because using Bayesian ended up with the following
P(S = N|F = N) P(F = N)/ P(S = N)
but from the diagram I have and as you can see from the probabilities, S depend on both F and T and in the expression above we...
I am having problem solving this exercise. The problem actually comes with a diagram but I do not know and I do not think i can draw it in the forum. The exercise is based on car starting(Heckerman 1995)
Since I can't draw the network diagram here but values of probability are given but...
Well I should have said this earlier.
The time series is a random Gaussian noise so Zt is independent and identically distributed. hence E[Zt] = 0 --> which is the expectation(mean) and E[(Zt)^2] = σ^2 --> expectation variance.
To answer your question the expectation of each term in the...
Is the following ARMA (2,1) model stationary?
xt + 1/6xt-1 – 1/3xt-2 = εt + 0.7εt-1
Inorder to know if a model is stationary. we check the mean, variance and the covariance and check whether it is dependent on time.
Obviously the mean is zero but my problem is how do i carry out the...
I am reading a topic on Bayesian Inference.I read books from different authors but they are all the same. I cannot see how the terms are derived.
Could anyone briefly explain what is going on and what is it that we are trying to find using this Bayesian. Bayesian is a combination of belief...
Regarding the previous question, am I on the right track? Thx.
Whoops sori i didnt know there was a next page.
Well briefly we have been taught on that Bayes theorem. But I should say the formula you gave is not familiar to me or I might have come across under maximum liklihood. I will...
probability that someone is either innocent or guilty can be written as
we know P(guilty) = 1/10000 so p(innocent) = 1 - (1/100000)
hence p(guilty or innocent) = p(guilty) + p(innocent)
probability that there is a DNA match and the person is either innocent or guilty can be written as...
Yes i agree that a person is innocent iff he is not guilty. but there is still a probabilty of a match although a person is innocent.
therefore shouldn't that be considered in the p(DNA match). Correct me if I am wrong. Thx..