Explained as: linear model

    Features with largest coefficients per class.
    Caveats:
    1. Be careful with features which are not
       independent - weights don't show their importance.
    2. If scale of input features is different then scale of coefficients
       will also be different, making direct comparison between coefficient values
       incorrect.
    3. Depending on regularization, rare features sometimes may have high
       coefficients; this doesn't mean they contribute much to the
       classification result for most examples.

y=Canada top features | y=HongKong top features | y=India top features | y=Ireland top features | y=Jamaica top features | y=Nigeria top features | y=Philippines top features | y=Singapore top features | y=SriLanka top features | y=USA top features
Weight? | Feature
--- | ---
+2.129 | canadians
+1.966 | employer
+1.944 | hannah
+1.783 | conventions
+1.665 | unclear
+1.651 | prairie
+1.608 | cegep
+1.581 | ash
+1.536 | we
+1.478 | biotechnology
+1.462 | concordia
+1.440 | scotia
+1.436 | cat
+1.411 | sshrc
+1.411 | provincial
+1.405 | nova
+1.362 | ui
+1.361 | information
+1.349 | groups
+1.347 | centre
… 15879 more positive …
… 49444 more negative …
-1.241 | road
-1.286 | was
-1.405 | mr
-1.961 | hope
-6.006 | can
Weight? | Feature
--- | ---
+2.151 | government
+2.101 | can
+2.022 | mr
+1.921 | body
+1.682 | wong
+1.663 | beijing
+1.661 | japanese
+1.649 | licence
+1.639 | mediation
+1.611 | yuen
+1.574 | political
+1.528 | chung
+1.509 | ch
+1.501 | kowloon
+1.468 | hkac
+1.446 | capitalism
+1.419 | diabetes
+1.395 | frank
+1.394 | po
+1.378 | deviant
… 15358 more positive …
… 47655 more negative …
-1.208 | state
-1.557 | this
-1.574 | country
-1.589 | national
-2.037 | that
Weight? | Feature
--- | ---
+1.442 | of
+0.817 | mabel
+0.806 | singh
+0.788 | subhro
+0.732 | narasimha
+0.722 | college
+0.699 | monolina
+0.692 | crore
+0.679 | duff
+0.672 | religion
+0.671 | prof
+0.670 | annuity
+0.659 | books
+0.658 | has
+0.656 | ayer
+0.639 | earth
+0.632 | wylie
+0.626 | line
+0.609 | letter
+0.608 | music
… 17822 more positive …
… 29508 more negative …
-0.499 | registrant
-0.596 | oil
-0.602 | for
-0.944 | that
-11.279 | in
Weight? | Feature
--- | ---
+3.445 | northern
+2.388 | ulster
+2.114 | christmas
+2.065 | cannabis
+1.824 | sign
+1.783 | groundwater
+1.668 | on
+1.628 | ail
+1.617 | in
+1.563 | narratives
+1.520 | garda
+1.514 | community
+1.503 | kay
+1.436 | queen
+1.419 | bullet
+1.405 | jude
+1.386 | xmas
+1.346 | ye
+1.340 | advice
+1.324 | turloughs
… 14395 more positive …
… 49248 more negative …
-1.004 | one
-1.009 | program
-1.018 | <BIAS>
-1.045 | am
-1.100 | teachers
Weight? | Feature
--- | ---
+2.756 | indies
+2.386 | st
+2.174 | mechtilde
+2.113 | am
+1.902 | clea
+1.803 | hi
+1.802 | energy
+1.788 | miss
+1.764 | seaga
+1.760 | west
+1.710 | persons
+1.632 | linguistics
+1.617 | water
+1.616 | mi
+1.605 | yuh
+1.600 | crab
+1.569 | campus
+1.568 | ml
+1.512 | shipping
+1.484 | mud
… 14187 more positive …
… 49770 more negative …
-1.141 | state
-1.156 | ll
-1.306 | it
-1.341 | ve
-1.343 | <BIAS>
Weight? | Feature
--- | ---
+2.381 | state
+2.261 | niger
+1.891 | corrosion
+1.872 | delta
+1.770 | kehinde
+1.765 | facebook
+1.750 | mazi
+1.739 | federal
+1.651 | donat
+1.606 | inec
+1.605 | breastfeeding
+1.585 | god
+1.584 | meaning
+1.570 | handicapped
+1.547 | drying
+1.541 | corruption
+1.467 | ekid
+1.456 | governor
+1.449 | urhobo
+1.448 | polio
… 13779 more positive …
… 46418 more negative …
-0.928 | these
-0.970 | program
-0.981 | don
-0.996 | time
-1.057 | an
Weight? | Feature
--- | ---
+1.779 | labor
+1.732 | cattle
+1.701 | la
+1.691 | nog
+1.654 | romina
+1.650 | center
+1.627 | edsa
+1.610 | metro
+1.594 | differance
+1.508 | president
+1.490 | milf
+1.487 | program
+1.484 | inez
+1.484 | sa
+1.459 | mindanao
+1.439 | percent
+1.422 | ang
+1.394 | levinas
+1.393 | object
+1.393 | influenza
… 15933 more positive …
… 51205 more negative …
-0.961 | programme
-1.039 | at
-1.084 | real
-1.114 | labour
-1.307 | students
Weight? | Feature
--- | ---
+1.885 | business
+1.807 | batik
+1.670 | population
+1.646 | editors
+1.584 | stuart
+1.552 | curriculum
+1.550 | tickets
+1.525 | jeremy
+1.522 | hence
+1.504 | lienhwa
+1.497 | satan
+1.487 | client
+1.481 | phonecards
+1.476 | tong
+1.464 | port
+1.458 | postscript
+1.448 | national
+1.436 | staff
+1.394 | straits
+1.391 | mental
… 15256 more positive …
… 48691 more negative …
-0.952 | our
-1.061 | people
-1.069 | summer
-1.227 | says
-1.853 | we
Weight? | Feature
--- | ---
+3.198 | ltte
+1.965 | plantation
+1.956 | in
+1.903 | negotiation
+1.902 | 2000
+1.896 | fashion
+1.808 | tamils
+1.796 | unp
+1.776 | ngo
+1.684 | ceylon
+1.658 | baby
+1.626 | nanotechnology
+1.617 | country
+1.598 | internet
+1.565 | tea
+1.551 | cholesterol
+1.525 | mudiyanse
+1.512 | india
+1.485 | rats
+1.449 | with
… 16614 more positive …
… 47413 more negative …
-0.955 | must
-0.978 | they
-1.106 | for
-1.139 | <BIAS>
-1.538 | or
Weight? | Feature
--- | ---
+2.095 | that
+1.754 | copyright
+1.659 | synderesis
+1.646 | program
+1.633 | apartment
+1.626 | postmodernism
+1.508 | stone
+1.448 | kids
+1.440 | cancer
+1.432 | woman
+1.355 | photography
+1.345 | fp
+1.335 | class
+1.333 | twilight
+1.328 | sommers
+1.323 | ireland
+1.321 | carbide
+1.276 | europe
+1.276 | novices
+1.251 | lucid
… 15848 more positive …
… 44849 more negative …
-1.411 | was
-1.690 | white
-2.080 | is
-2.134 | university
-2.899 | us