So created a little program using mallet's API following this example in the developer's guide. However, I do not understand the final weight output.
While the program is running it is outputting reasonable weights to each topic(see below):
Mallet LDA: 20 topics, 5 topic bits, 11111 topic mask
max tokens: 5179
total tokens: 31712
<10> LL/token: -7,88809
<20> LL/token: -7,54327
<30> LL/token: -7,44727
<40> LL/token: -7,3755
0 0,5 parses files browser creates selects docking entity
1 0,5 boolean listener handles enabled directory mouse lines
2 0,5 text area selected inserts creates deletes user
3 0,5 int line offset caret screen moves end
4 0,5 creates node container widget namespace block grid
5 0,5 selection key event processes shows word start
6 0,5 boolean search index indent hyper bundle dialog
7 0,5 string element adds starts ends reader map
8 0,5 handles changed message properties mode content loads
9 0,5 creates fold plugin list marker model handler
10 0,5 action set invokes edit creates char token
11 0,5 pane option saves inits error save creates
12 0,5 component adds size layout removes dockable window
13 0,5 converts type view tostring rule parser closes
14 0,5 buffer update updates handles status invalidates byte
15 0,5 evals creates menu callstack eval inits document
16 0,5 class manager path url bsh impl chunk
17 0,5 handles variable expression color property primitive icon
18 0,5 file creates vfs request literal parent runs
19 0,5 string parse editor.getexpansion preferredlayoutsize(parent preprocesskeyevent startlinecomment getstringproperty
[...]
0 0,07447 parses string files entity selected decl lists
1 0,09965 handles boolean listener adds mouse enabled drag
2 0,09124 text area selected selects user input int
3 0,14501 int line offset screen start count end
4 0,07821 node creates container widget closes namespace grid
5 0,05882 key event selection processes viewer extends handles
6 0,16431 boolean indent list index equals updates modifiers
7 0,08873 element string starts ends adds document map
8 0,14141 handles changed message properties mode content loads
9 0,12078 fold creates plugin marker model handler list
10 0,11112 action creates invokes edit set token stream
11 0,11896 option pane inits saves view creates color
12 0,11379 component layout size adds dockable window removes
13 0,11022 string converts tostring type char marks segment
14 0,10636 buffer update handles updates byte status edit
15 0,11183 evals creates menu callstack error eval reader
16 0,09098 class path url manager impl classes loader
17 0,09077 handles variable expression property creates bsh primitive
18 0,12605 file string search vfs dialog creates literal
19 0,02491 string parse setvalueat disposedockablewindow getpreviousbuffer buffered rewinds
[beta: 0,02113]
<500> LL/token: -6,90397
Total time: 16 seconds
However, when it comes to the final output this comes out:
0 0.000 parses (115) string (90) files (53) entity (33) selected (29)
1 0.000 handles (110) boolean (82) listener (71) mouse (48) adds (44)
2 0.000 text (230) area (126) selected (61) user (28) selects (27)
3 0.000 int (588) line (295) offset (67) screen (54) start (49)
4 0.000 node (71) creates (48) widget (34) closes (33) container (32)
5 0.000 key (130) event (110) selection (81) processes (67) viewer (17)
6 0.000 boolean (586) indent (55) index (51) list (51) updates (23)
7 0.000 element (99) string (76) starts (48) ends (46) adds (43)
8 0.000 handles (464) changed (153) message (150) properties (96) mode (96)
9 0.000 fold (108) creates (107) plugin (97) marker (56) model (55)
10 0.000 action (132) creates (89) invokes (64) set (61) edit (58)
11 0.000 option (119) pane (118) inits (114) saves (77) view (68)
12 0.000 component (128) adds (89) layout (87) size (76) dockable (63)
13 0.000 string (488) converts (114) tostring (65) type (41) char (30)
14 0.000 buffer (289) update (89) handles (71) updates (49) byte (30)
15 0.000 evals (157) creates (121) menu (102) callstack (92) error (66)
16 0.000 class (243) path (76) url (47) manager (42) impl (28)
17 0.000 handles (134) variable (79) expression (73) creates (47) property (46)
18 0.000 file (126) string (111) search (89) vfs (64) int (52)
19 1.000 string (2705) parse (2605) parser.reinittokeninput(in (1) image (1) candidates[i (1)
0 0.930564405720232
All the weights are marked as 0 except for that is marked as one. Can anyone explain what is going on here?
The code you're pointing to is printing out the topic distribution for the first document, which is almost 100% allocated to topic 19.
It looks like the collection is very small (30k words) and the documents are rather large (up to 5k). If there are more topics than documents, the model can maximize its objective by putting each document in its own topic.
You will get better results from more documents, and may need to consider breaking documents into smaller chunks. LDA works best when each segment is short enough that it could reasonably be assumed to have a homogenous mix of themes. In other words, you wouldn't expect the beginning of the segment to be about something different than the end of the segment. 200-500 words is a typical range. 300,000 total tokens is also probably about the minimum that you could expect good results.