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This is a directory of classifiers that have been published by users.
Public classifiers (30)
Determines the tonality of a text - corporate (formal) or personal (informal). Helps distinguish between prosumer media and pro media for instance.
Currently works for English texts.
22636
total classifications
379
last seven days
The state of mind of the writer - upset or happy. On the extreme side there is angry, hateful writers and on the other extreme there is joyful and loving writers.
The measured accuracy is 96% (using 10-fold cross validation). For reliable results we recommend that you use at least 200 words.
Currently works for English texts.
41447
total classifications
392
last seven days
Determines the Sensing/iNtuition dimension of the personality type according to Myers-Briggs personality model. The analysis is based on the writing style and should NOT be confused with the MBTI (c) which determines personality type based on self-assessment questionnaires.
Currently works for English texts. Swedish version available on request.
17044
total classifications
7
last seven days
Determines the Thinking/Feeling dimension of the personality type according to Myers-Briggs personality model. The analysis is based on the writing style and should NOT be confused with the MBTI (c) which determines personality type based on self-assessment questionnaires.
Currently works for English texts. Swedish version available on request.
17003
total classifications
7
last seven days
Analyzes the Extraversion/Introversion dimension of the personality type according to Myers-Briggs personality model. The analysis is based on the writing style and should NOT be confused with the MBTI (c) which determines personality type based on self-assessment questionnaires.
Currently works for English texts. Swedish version available on request.
16101
total classifications
6
last seven days
Determines the Judging/Perceiving dimension of the personality type according to Myers-Briggs personality model. The analysis is based on the writing style and should NOT be confused with the MBTI (c) which determines personality type based on self-assessment questionnaires.
Currently works for English texts. Swedish version available on request.
16118
total classifications
7
last seven days
Classifies alternative treatmeant methods into four types according to body/mind-orientation and if it is corrective or nurturing in orientation. There is also a class for theoretical models related to treatments so that they can be sorted out.
15940
total classifications
1
last seven days
Classifies the language of a text by looking on about 4000 commonly used words per language. It works best with clean texts but can also be used for HTML pages. For reliable results HTML pages need more text content (since HTML often contains English words and comments).
2120676
total classifications
30336
last seven days
This news categorizer is only a simple example used in a tutorial. It has been trained on 20 texts per category (sports, entertainment and science) so don't expect too much (even though it seems to do incredibly well).
15971
total classifications
0
last seven days
This classifier tries to estimate to which age group a blog belongs. The training data is based upon about 7000 blogs collected randomly from Internet.
24028
total classifications
517
last seven days
Categories an English text into a topic (Arts, Business, Computers, Games, Health, Home, Recreation, Science, Society and Sports). Each of those topics has more specific child classifier (Art Topics, Business Topics etc).
It uses a subset of topics from the Open Directory Project at http://www.dmoz.org.
89
total classifications
10
last seven days
Categories an English text into an art topic. Use the parent classifier 'Topics' to find out if a text belongs in this category.
It uses a subset of topics from the Open Directory Project at http://www.dmoz.org.
23
total classifications
0
last seven days
Categories an English text into an business topic. Use the parent classifier 'Topics' to find out if a text belongs in this category. It uses a subset of topics from the Open Directory Project at http://www.dmoz.org.
4
total classifications
0
last seven days
Categories an English text into a computer topic. Use the parent classifier 'Topics' to find out if a text belongs in this category. It uses a subset of topics from the Open Directory Project at http://www.dmoz.org.
17
total classifications
0
last seven days
Categories an English text into a game topic. Use the parent classifier 'Topics' to find out if a text belongs in this category. It uses a subset of topics from the Open Directory Project at http://www.dmoz.org.
5
total classifications
0
last seven days
Categories an English text into a health topic. Use the parent classifier 'Topics' to find out if a text belongs in this category. It uses a subset of topics from the Open Directory Project at http://www.dmoz.org.
16
total classifications
0
last seven days
Categories an English text into a home topic. Use the parent classifier 'Topics' to find out if a text belongs in this category. It uses a subset of topics from the Open Directory Project at http://www.dmoz.org.
4
total classifications
0
last seven days
Categories an English text into a recreation topic. Use the parent classifier 'Topics' to find out if a text belongs in this category. It uses a subset of topics from the Open Directory Project at http://www.dmoz.org.
10
total classifications
1
last seven days
Categories an English text into a science topic. Use the parent classifier 'Topics' to find out if a text belongs in this category. It uses a subset of topics from the Open Directory Project at http://www.dmoz.org.
8
total classifications
0
last seven days
Categories an English text into a society topic. Use the parent classifier 'Topics' to find out if a text belongs in this category. It uses a subset of topics from the Open Directory Project at http://www.dmoz.org.
9
total classifications
0
last seven days
Categories an English text into a sport topic. Use the parent classifier 'Topics' to find out if a text belongs in this category. It uses a subset of topics from the Open Directory Project at http://www.dmoz.org.
5
total classifications
0
last seven days
This classifier tries to figure out if a text is written by a male or female. It has been trained on 11000 blogs (5500 blogs wrtten by females and 5500 by males). More text gives better results.
45058
total classifications
2123
last seven days
This classifier has been trained on 21 different classical authors. We have used about three books per author collected from the Gutenberg project. It only works for English texts.
Try it out to see which poet your blog or text is most alike!
159498
total classifications
21684
last seven days
4
total classifications
0
last seven days
Classification between Semantic/pragmatic puns and phonological puns
15933
total classifications
0
last seven days
kvista's librarything classifier
16
total classifications
0
last seven days
2
total classifications
0
last seven days
there are three types of websites in the world.
20
total classifications
0
last seven days
To tell the difference between Apple the Fruit and Apple Computer
25
total classifications
0
last seven days
www.MyTwiShirt.com is your only source for twiShirts. A "twishirt" is a t-shirt with your Twitter username and photo on it (just in case you didn't guessed it already :). The process is really simple, you sign in with your Twitter account and get your twiShirt instantly. During the process we automatically detect your gender based on your tweets, and you're giving you 10% price deal for just one tweet. The shipping is done by Zazzle, world leader in print-on-demand services.
2
total classifications
2
last seven days