critiques

There's good potential here. Here are my scores, with comments below. Let me know if you want to discuss any of the points.

Scale of 1 to 5, where 1 = strongly disagree and 5 = strongly agree:

(5) The topic is relevant for the course.
(2) The writing is clear and the English is good.
(4) The page is written at an appropriate level for CPSC 522 students (where the students have diverse backgrounds).
(2) The formalism (definitions, mathematics) was well chosen to make the page easier to understand.
(2) The abstract is a concise and clear summary.
(2.5) There were appropriate (original) examples that helped make the topic clear.
(3) There was appropriate use of (pseudo-) code.
(4) It had a good coverage of representations, semantics, inference and learning (as appropriate for the topic).
(5) It is correct.
(4) It was neither too short nor too long for the topic.
(5) It was an appropriate unit for a page (it shouldn't be split into different topics or merged with another page).
(1) It links to appropriate other pages in the wiki.
(3) The references and links to external pages are well chosen.
(2) I would recommend this page to someone who wanted to find out about the topic.
(2) This page should be highlighted as an exemplary page for others to emulate.

Comments:

Proofreading is recommended, as there are grammatical errors throughout that make the page harder to read; this is more of a problem given the low text-to-math ratio.
Centering the formulas makes the page harder to read. You can indent the formulas by starting a line with ':'.
I think were supposed to use the built-in math tags to enter formulas instead of images.
There's a consistent pattern of giving a definition/algorithm before motivating it; this results in a disjointed flow that can be difficult to follow.
I didn't see any links to other pages in the wiki.

Abstract:

This is more of an introduction than an abstract. The abstract should contain a summary of the page contents, and the introduction currently there would be better placed in the content section.
I believe the HMM page is mentioned in the Graphical Models and Bayesian Networks page, so it might be good to have links to those in the "Builds on" section.

Definition of HMM:

It feels like the goal is to have as little text as possible. If I knew nothing about HMMs, I'd have difficulty understanding this section. Having more qualitative descriptions, perhaps with figures, would be useful here.
"All possible states" and "all possible observations" reads as very universal. You should specify that you're talking about some system that can be in any one of N states, and that at any time, one of M observations can be made; then that you're making observations at T different time steps, so that at each time step the system is in state i_t with observation o_t.
If someone doesn't know what a state transposition probability matrix is, then they also wouldn't know why they need one. As previous, it would be good to motivate its existence by talking about how, when the system is in state i, it can transition into state j with some probability p; and that it's useful to us to collect these probabilities into a matrix that we call...
Similarly for the output matrix and initial state vector: motivate/describe them before you give the math.

Example:

The example you chose is a good one, as it can be used to illustrate the concepts very well.
The description of the rules would be better put as a caption to a state transition diagram (as a figure).
Tables 2 and 3 should be explicitly mentioned in the text of the example; a reader wouldn't know to look for them and might easily get confused.

Three core problems of HMM:

The hierarchy of section headings seems to break down in here, so it's hard to tell what is a subsection of what.
You should mention that the forward-backward algorithm consists of a forward procedure and a backward procedure, so that people expect those headings.
It would be very useful to continue the ball example through this section so that people have an example of how the calculations are carried out.
You discuss the/an Expectation Maximization algorithm, which is what I expect to see next, but instead the Baum-Welch algorithm is given, which has not yet been mentioned.
"Viterbi", not "Veterbi".

JordonJohnson (talk)‎

Hi Jordan,

Thank you for your detailed critique, it really helps me a lot in improving my page.I have fixed questions you pointed out, if you have further suggestions, please let me know. Thanks a lot!

Best regards, Jiahong Chen

JiahongChen (talk)‎