Are Deep Neural Networks Dramatically Overfitted? (from this blog)
- I would like to discuss a couple of papers on generalizability and complexity measurement of deep learning models in the post. Hopefully, it could shed light on your thinking path towards the understanding of why DNN can generalize.
Work for the next week:
- I need to build a set of panalyzers that are room/channel specific. Done!
- It looks like it’s just creating a key in the channel loop that also has the split information:
max = len(split_list)-1 for i in range(0, max): for db in db_list: name_list = self.run_query('select username as new, id as old from user_view', db_name=db) for group in channel_list: key = "splt-chn_({}of{})-{}".format(i+1, max, group)
- It looks like it’s just creating a key in the channel loop that also has the split information:
- Comparing the counts of place and space terms will (hopefully!) show the movement of the channel population between splits (splits should be similar across channels), and the actions (spaces) that are explored in each space.
- Table that shows place/space term counts by channel and split
- I think I can get this by just using the top-n common terms to identify the rooms, and the top-n (excluding room terms) for each splt-chn panalyzer. These room terms are the identifier (row label), and then each column is a different group, which gives us a set of 4 room nodes from which link to action nodes. Take that and output to graph?
- Refining the table and graph can be done by finding embedding neighbors.
- Statistical difference in the populations of place terms within each split and within each channel.
- What is the math that we use to show spaces? Or do we just show that they are different from the place populations?
- Build a map from the table
Well that’s a nice way to start the day:
---------------------- split_1_of_4: subject BOW tymora1: 3948 tymora2: 732 tymora3: 506 Group: 63 1: 63 post BOW goblin: 287 room: 239 orc: 227 stairs: 214 vines: 197 hit: 186 fire: 171 arrow: 170 gate: 134 behind: 133 ---------------------- split_2_of_4: subject BOW tymora1: 3972 tymora2: 732 tymora3: 376 Group: 83 1: 83 post BOW rope: 415 gate: 331 room: 324 orb: 309 statues: 251 across: 207 side: 196 around: 162 pit: 150 feet: 148 ---------------------- split_3_of_4: subject BOW tymora1: 3004 tymora2: 816 tymora3: 1016 Group: 57 1: 57 post BOW troll: 618 grogg: 596 chest: 274 hand: 252 room: 244 open: 209 gate: 199 club: 191 want: 169 key: 143 ---------------------- split_4_of_4: subject BOW tymora1: 596 tymora2: 162 tymora3: 438 Group: 67 1: 67 post BOW dragon: 176 coins: 174 room: 148 barrier: 108 light: 102 something: 102 platform: 100 eyes: 82 woman: 82 treasure: 62
Need to fix the “Group” “1” error and add an underscore to subjects in panalyzers – done
Note. This means that you left a paren on your callback: File "C:/Development/AntibubblesDungeon/src/analytics/SequenceAnalyzerGUI.py", line 438, in show_bow self.main_text.delete('1.0', END) AttributeError: 'NoneType' object has no attribute 'delete'
Added the beginnings of the table