jonas/nlp-lab
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

evaluation anpassungen

Browse Source
This commit is contained in:
Carsten 2018-07-20 13:46:12 +02:00
parent a4f82aadb5
commit b452b2a918
12 changed files with 365 additions and 298 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

26
Carsten_Solutions/Emoji-Emoticon-Assignment_new.csv Normal file
View File

@ -0,0 +1,26 @@
Icon,Icon,Icon,Icon,Icon,Icon,Icon,Icon,Icon,Icon,Icon,Emoji,Meaning
:‑) :),:-] :],:-3 :3,:-> :>,8-) 8),:-} :},:o),:c),:^),=],=),☺️🙂😊😀😁,Smiley or happy face.[4][5][6]
:‑D :D,8‑D 8D,x‑D xD,X‑D XD,=D,=3,B^D,,,,,😃😄😆😍,"Laughing,[4] big grin,[5][6] laugh with glasses,[7] or wide-eyed surprise[8]"
:-)),:-)),:-)),:-)),:-)),:-)),:-)),:-)),:-)),:-)),:-)),,Very happy or double chin[7]
:‑( :(,:‑c :c,:‑< :<,:‑[ :[,:-||,>:[,:{,:@,>:(,,,☹️🙁😠😡😞😟😣😖,"Frown,[4][5][6] sad,[9] angry,[7] pouting"
:'‑( :'(,:'‑( :'(,:'‑( :'(,:'‑( :'(,:'‑( :'(,:'‑( :'(,:'‑( :'(,:'‑( :'(,:'‑( :'(,:'‑( :'(,:'‑( :'(,😢😭,Crying[9]
:'‑) :'),:'‑) :'),:'‑) :'),:'‑) :'),:'‑) :'),:'‑) :'),:'‑) :'),:'‑) :'),:'‑) :'),:'‑) :'),:'‑) :'),😂,Tears of happiness[9]
D‑':,D:<,D:,D8,D;,D=,DX,,,,,😨😧😦😱😫😩,"Horror, disgust, sadness, great dismay[5][6] (right to left)"
:‑O :O,:‑o :o,:-0,8‑0,>:O,,,,,,,😮😯😲,"Surprise,[3] shock,[4][10] yawn[11]"
:-* :*,:×,,,,,,,,,,😗😙😚😘😍,Kiss
;‑) ;),*-) *),;‑] ;],;^),":‑,",;D,,,,,,😉😜😘,"Wink,[4][5][6] smirk[10][11]"
:‑P :P,X‑P XP,x‑p xp,:‑p :p,:‑Þ :Þ,:‑þ :þ,:‑b :b,d:,=p,>:P,,😛😝😜🤑,"Tongue sticking out, cheeky/playful,[4] blowing a raspberry"
:‑/ :/,:‑.,>:\,>:/,:\,=/,=\,:L,=L,:S,,🤔😕😟,"Skeptical, annoyed, undecided, uneasy, hesitant[4]"
:‑| :|,,,,,,,,,,,😐😑,"Straight face[5] no expression, indecision[9]"
:$,,,,,,,,,,,😳😞😖,"Embarrassed,[6] blushing[7]"
:‑X :X,:‑# :#,:‑& :&,,,,,,,,,🤐😶,"Sealed lips or wearing braces,[4] tongue-tied[9]"
O:‑) O:),0:‑3 0:3,0:‑) 0:),0;^),,,,,,,,😇👼,"Angel,[4][5][10] saint,[9] innocent"
>:‑) >:),}:‑) }:),3:‑) 3:),>;),,,,,,,,😈,"Evil,[5] devilish[9]"
|;‑),|‑O,,,,,,,,,,😎😪,"Cool,[9] bored/yawning[10]"
:‑J,:‑J,:‑J,:‑J,:‑J,:‑J,:‑J,:‑J,:‑J,:‑J,:‑J,😏😒,Tongue-in-cheek[12]
#‑),#‑),#‑),#‑),#‑),#‑),#‑),#‑),#‑),#‑),#‑),—,Partied all night[9]
%‑) %),%‑) %),%‑) %),%‑) %),%‑) %),%‑) %),%‑) %),%‑) %),%‑) %),%‑) %),%‑) %),😵😕🤕,"Drunk,[9] confused"
:‑###.. :###..,:‑###.. :###..,:‑###.. :###..,:‑###.. :###..,:‑###.. :###..,:‑###.. :###..,:‑###.. :###..,:‑###.. :###..,:‑###.. :###..,:‑###.. :###..,:‑###.. :###..,🤒😷🤢,Being sick[9]
<:‑|,<:‑|,<:‑|,<:‑|,<:‑|,<:‑|,<:‑|,<:‑|,<:‑|,<:‑|,<:‑|,—,"Dumb, dunce-like[10]"
"',:-|","',:-l",,,,,,,,,,🤨,"Scepticism, disbelief, or disapproval[13][14]"
<_<,>_>,,,,,,,,,,,Sideways look. Devious or guilty.
1 Icon Icon Icon Icon Icon Icon Icon Icon Icon Icon Icon Emoji Meaning
2 :‑) :) :-] :] :-3 :3 :-> :> 8-) 8) :-} :} :o) :c) :^) =] =) ☺️🙂😊😀😁 Smiley or happy face.[4][5][6]
3 :‑D :D 8‑D 8D x‑D xD X‑D XD =D =3 B^D 😃😄😆😍 Laughing,[4] big grin,[5][6] laugh with glasses,[7] or wide-eyed surprise[8]
4 :-)) :-)) :-)) :-)) :-)) :-)) :-)) :-)) :-)) :-)) :-)) Very happy or double chin[7]
5 :‑( :( :‑c :c :‑< :< :‑[ :[ :-|| >:[ :{ :@ >:( ☹️🙁😠😡😞😟😣😖 Frown,[4][5][6] sad,[9] angry,[7] pouting
6 :'‑( :'( :'‑( :'( :'‑( :'( :'‑( :'( :'‑( :'( :'‑( :'( :'‑( :'( :'‑( :'( :'‑( :'( :'‑( :'( :'‑( :'( 😢😭 Crying[9]
7 :'‑) :') :'‑) :') :'‑) :') :'‑) :') :'‑) :') :'‑) :') :'‑) :') :'‑) :') :'‑) :') :'‑) :') :'‑) :') 😂 Tears of happiness[9]
8 D‑': D:< D: D8 D; D= DX 😨😧😦😱😫😩 Horror, disgust, sadness, great dismay[5][6] (right to left)
9 :‑O :O :‑o :o :-0 8‑0 >:O 😮😯😲 Surprise,[3] shock,[4][10] yawn[11]
10 :-* :* :× 😗😙😚😘😍 Kiss
11 ;‑) ;) *-) *) ;‑] ;] ;^) :‑, ;D 😉😜😘 Wink,[4][5][6] smirk[10][11]
12 :‑P :P X‑P XP x‑p xp :‑p :p :‑Þ :Þ :‑þ :þ :‑b :b d: =p >:P 😛😝😜🤑 Tongue sticking out, cheeky/playful,[4] blowing a raspberry
13 :‑/ :/ :‑. >:\ >:/ :\ =/ =\ :L =L :S 🤔😕😟 Skeptical, annoyed, undecided, uneasy, hesitant[4]
14 :‑| :| 😐😑 Straight face[5] no expression, indecision[9]
15 :$ 😳😞😖 Embarrassed,[6] blushing[7]
16 :‑X :X :‑# :# :‑& :& 🤐😶 Sealed lips or wearing braces,[4] tongue-tied[9]
17 O:‑) O:) 0:‑3 0:3 0:‑) 0:) 0;^) 😇👼 Angel,[4][5][10] saint,[9] innocent
18 >:‑) >:) }:‑) }:) 3:‑) 3:) >;) 😈 Evil,[5] devilish[9]
19 |;‑) |‑O 😎😪 Cool,[9] bored/yawning[10]
20 :‑J :‑J :‑J :‑J :‑J :‑J :‑J :‑J :‑J :‑J :‑J 😏😒 Tongue-in-cheek[12]
21 #‑) #‑) #‑) #‑) #‑) #‑) #‑) #‑) #‑) #‑) #‑) — Partied all night[9]
22 %‑) %) %‑) %) %‑) %) %‑) %) %‑) %) %‑) %) %‑) %) %‑) %) %‑) %) %‑) %) %‑) %) 😵😕🤕 Drunk,[9] confused
23 :‑###.. :###.. :‑###.. :###.. :‑###.. :###.. :‑###.. :###.. :‑###.. :###.. :‑###.. :###.. :‑###.. :###.. :‑###.. :###.. :‑###.. :###.. :‑###.. :###.. :‑###.. :###.. 🤒😷🤢 Being sick[9]
24 <:‑| <:‑| <:‑| <:‑| <:‑| <:‑| <:‑| <:‑| <:‑| <:‑| <:‑| — Dumb, dunce-like[10]
25 ',:-| ',:-l 🤨 Scepticism, disbelief, or disapproval[13][14]
26 <_< >_> Sideways look. Devious or guilty.

1
Project/Assignment_emoticon_emoji_backup.txt Normal file
View File

@ -0,0 +1 @@
[[':c)', '☺'], [':c)', '☺'], [':-3', '😊'], [':-}', '☺'], [':>', '☺'], ['=)', '☺'], [':‑)', '☺'], [':^)', '😊'], ['8)', '☺'], [':}', '☺'], [':->', '☺'], [':-]', '☺'], [':]', '☺'], ['=]', '☺'], [':o)', '☺'], [':)', '☺'], ['8-)', '☺'], [':3', '☺'], ['xD', '😆'], ['x‑D', '😆'], ['=3', '😃'], ['B^D', '😄'], ['XD', '😆'], ['=D', '😃'], ['8‑D', '😃'], [':‑D', '😃'], ['8D', '😃'], [':D', '😃'], ['X‑D', '😆'], [':‑[', '🙁'], [':@', '😡'], [':‑(', '🙁'], [':(', '🙁'], [':{', '🙁'], [':‑<', '🙁'], ['>:(', '😡'], [':c', '☹'], [':<', '☹'], [':‑c', '☹'], ['>:[', '😡'], [':-||', '🙁'], [':[', '🙁'], [":'‑(", '😢'], [":'(", '😢'], [":')", '😂'], [":'‑)", '😂'], ['DX', '😫'], ['D:', '😧'], ['D:<', '😩'], ['D8', '😦'], ['D=', '😦'], ['D;', '😩'], ["D‑':", '😨'], [':-0', '😮'], [':‑O', '😮'], [':o', '😮'], [':O', '😮'], [':‑o', '😮'], ['>:O', '😲'], ['8‑0', '😮'], [':×', '😘'], [':*', '😘'], [':-*', '😘'], [';]', '😉'], [';)', '😉'], [';‑)', '😉'], ['*-)', '😜'], [';^)', '😜'], [';D', '😜'], [';‑]', '😉'], ['*)', '😜'], [':‑,', '😘'], [':‑Þ', '😛'], [':þ', '😛'], [':‑þ', '😛'], [':‑b', '😛'], ['x‑p', '😝'], ['>:P', '😜'], ['XP', '😝'], [':Þ', '😛'], [':P', '😛'], ['xp', '😝'], [':b', '😛'], ['=p', '😛'], ['d:', '😛'], [':p', '😛'], [':‑p', '😛'], [':‑P', '😛'], ['X‑P', '😝'], [':\\', '🤔'], ['>:/', '🤔'], [':/', '🤔'], ['=\\', '🤔'], [':L', '😕'], [':S', '😕'], [':‑/', '🤔'], ['=L', '😕'], [':‑.', '🤔'], ['=/', '😕'], ['>:\\', '🤔'], [':‑|', '😐'], [':|', '😐'], [':$', '😳'], [':&', '😶'], [':‑X', '🤐'], [':#', '🤐'], [':‑#', '🤐'], [':‑&', '🤐'], [':X', '🤐'], ['0;^)', '😇'], ['0:‑3', '😇'], ['O:‑)', '😇'], ['0:)', '😇'], ['0:3', '😇'], ['0:‑)', '😇'], ['O:)', '😇'], ['3:)', '😈'], ['>:‑)', '😈'], ['>:)', '😈'], ['>;)', '😈'], ['}:)', '😈'], ['}:‑)', '😈'], ['3:‑)', '😈'], ['|‑O', '😪'], ['|;‑)', '😪'], [':‑J', '😏'], ['%‑)', '😵'], ['%)', '😵'], [':###..', '🤢'], [':‑###..', '🤢'], ["',:-|", '\U0001f928'], ["',:-l", '\U0001f928']]

135
Project/Tools/EmojiCounting.ipynb
View File

File diff suppressed because one or more lines are too long

BIN
Project/Tools/Emoticon Emoji space -- positive-negative-plot.png
View File

Binary file not shown.
Side by Side Swipe Overlay

Before

Width:  |  Height:  |  Size: 91 KiB

After

Width:  |  Height:  |  Size: 58 KiB

BIN
Project/Tools/Emoticon Emoji space -- sentiment-plot.png
View File

Binary file not shown.
Side by Side Swipe Overlay

Before

Width:  |  Height:  |  Size: 88 KiB

After

Width:  |  Height:  |  Size: 54 KiB

194
Project/Tools/Evaluation Sentences - Tabellenblatt1.csv
View File

@ -1,97 +1,97 @@
Sentence,prediction,topic hit,sentiment hit,both,ranked Sentence prediction topic hit sentiment hit both ranked
Hi how are you?,,,,, 0 Hi how are you? 😁😂😌😎😅😉🙌🤟
do you've got time,,,,, 1 do you've got time 😌😁😎😂🙌🤸🚯🤟
I go out for party tonight,,,,, 2 I go out for party tonight 😂😅😁😌🔰🔢🔣🔤
I'll take the bus or train,,,,, 3 I'll take the bus or train 😂😅😢😭🚆🚄🤘🤣
You look gorgeous in this dress,,,,, 4 You look gorgeous in this dress 😌🙌😀😎👗👥👤🤵
How hard was the exam,,,,, 5 How hard was the exam 😂😅😁😌😎😉🤘🤣
please can you give me some stuff,,,,, 6 please can you give me some stuff 😂😅😁😉😎😏🤙🤟
whats your name,,,,, 7 whats your name 😂😅😁😢😌😎😉📛
where are you from,,,,, 8 where are you from 😂😅😁😢😌😉😎🤟
what is your favourite color,,,,, 9 what is your favourite color 😌🙌😀😎😁😊😋😉
Do you like to play soccer this evening,,,,, 10 Do you like to play soccer this evening 😅😂😢😭😁😔⚽🤟
do you have any pets,,,,, 11 do you have any pets 😂😅😁😢😌🤸🚯🤟
I watch television all day,,,,, 12 I watch television all day 😂😅😢😁😉😌😎⌚
there some fake news but most of the time i dont care,,,,, 13 there some fake news but most of the time i dont care 😂😅😁😌🤘🗾🗽💩
i you fucking kidding,,,,, 14 i you fucking kidding 😂😅😢😁🤟🇮🇴🇼
i we have to hand in our report,,,,, 15 i we have to hand in our report 😌😁😎🙌✋🤟👊👋
is the world real,,,,, 16 is the world real 😂😅😁😉😎😌🤘🤣
i am you father,,,,, 17 i am you father 😂😅😢😭🎅🤟🇴🇼
is this a true cite,,,,, 18 is this a true cite 😂😅😁😌😢😘🇦💠
i like working for my phd,,,,, 19 i like working for my phd 😂😅😢😁🔢🔣🔰🇩
I at the end of my Master studes,,,,, 20 I at the end of my Master studes 😅😂😢😭🤘🗽🍲🥩
I like chilling with my friends outside,,,,, 21 I like chilling with my friends outside 😂😅😁😉📶🥤💘💝
are we allowed to extend our presentation time to 35min,,,,, 22 are we allowed to extend our presentation time to 35min 😌😁😂😅😎😉🙌🎁
yes you are because today there no other groups presenting,,,,, 23 yes you are because today there no other groups presenting 😌🙌😀😊🎁🚷⛔🚳
i would love if we needn't write a report,,,,, 24 i would love if we needn't write a report 😁😂😌😅💌🏩🤟😘
"no sorry, you have to wirite one.",,,,, 25 no sorry, you have to wirite one. 😢😭😅😔⛔🚳🚷🔞
"ALso Google Docs is not enough, you shell use share latex for your document",,,,, 26 ALso Google Docs is not enough, you shell use share latex for your document 😂😅😁😌🐚🔢🔣🔰
I'll hope we get a good grade,,,,, 27 I'll hope we get a good grade 😁😎😌😉😘🇦🙅💠
I'll really could imagine working in NLP in the feature,,,,, 28 I'll really could imagine working in NLP in the feature 😂😅😢😁👤⛳👥🤵
The weather today is really nice,,,,, 29 The weather today is really nice 😂😅😢😭😁😉🤘🤣
I like to take my dog out for a walk,,,,, 30 I like to take my dog out for a walk 😅😂😢😭🐕🐶🌭😘
I am a huge soccer fan,,,,, 31 I am a huge soccer fan 😂😌😁😅⚽😘🇦💠
I just hate bad tutorials,,,,, 32 I just hate bad tutorials 😢😅😂😭😔😤😁😌
I am so glad I bought new shoes yesterday,,,,, 33 I am so glad I bought new shoes yesterday 😁😎😌😉🆕🥿👞👠
My mom likes ice cream,,,,, 34 My mom likes ice cream 😌😁😎🙌🍨🍦🍧🏒
This so so much work...,,,,, 35 This so so much work... 😅😂😢😭😔😁😌😤
I want to have holidays,,,,, 36 I want to have holidays 😅😂😢😁😭😌😎😉
Please come to my birthday party,,,,, 37 Please come to my birthday party 😂😁😌😅😎😉🙌🎂
why are some people just not replying to emails,,,,, 38 why are some people just not replying to emails 😂😅😁😉😎😌😏🚯
I am sick of studying,,,,, 39 I am sick of studying 😢😅😭😂🗾🧵🧶🥛
Living in Germany can be expensive,,,,, 40 Living in Germany can be expensive 😂😅😢😭👤🤵⛳👥
I love my new Iphone,,,,, 41 I love my new Iphone 😌😎😁😀🆕💌🏩🌑
Teddy bears are cute,,,,, 42 Teddy bears are cute 😌🙌😀😁😎😊🐻🧸
The sun is shining today,,,,, 43 The sun is shining today 😂😅😁😉⛅🌞🤘🤣
I am really stressed out,,,,, 44 I am really stressed out 😅😢😂😭😔😤😁😏
Mensa food is disgusting,,,,, 45 Mensa food is disgusting 😂😅😁😌🥫🍲🥘😋
I am so disappointed of this lecture,,,,, 46 I am so disappointed of this lecture 😂😅😁😌🗾🧵🧶🥛
I usually take my bike to work,,,,, 47 I usually take my bike to work 😅😂😁😌😎😉😢🙌
"This is so sad, I am almost crying",,,,, 48 This is so sad, I am almost crying 😢😭😅😔😂😤😩😒
My car broke down yesterday,,,,, 49 My car broke down yesterday 😅😂😢😭🚋🚓🚃👎
What is the usual time of study in Germany?,,,,, 50 What is the usual time of study in Germany? 😂😅😢😭🤘🗽🗾🤵
I try to eat healthy,,,,, 51 I try to eat healthy 😂😅😢😁😌😉😎😭
"Seeing people getting good marks with no effort, makes me angry",,,,, 52 Seeing people getting good marks with no effort, makes me angry 😂😅😁😢🙅🚷❌🚳
Live long and prosper,,,,, 53 Live long and prosper 😂😅😢😁🏹🍴🏀🔩
i love books about wizards,,,,, 54 i love books about wizards 😁😌😎😉📚📘📖📕
No one understands me,,,,, 55 No one understands me 😂😅😁😢🤙🕐🤪🔉
Why do we even have to study?,,,,, 56 Why do we even have to study? 😅😂😢😁😭😌🤸🚯
Tonight I will go drinking,,,,, 57 Tonight I will go drinking 😂😅😢😁😌😉😎🍹
Lets have a party,,,,, 58 Lets have a party 😂😅😁😌😎😘🇦💠
I dont think there is any bias in these sentences,,,,, 59 I dont think there is any bias in these sentences 😂😅😁😌👤🤵⛳👥
I really like to get this freedom in our work,,,,, 60 I really like to get this freedom in our work 😅😂😢😭👤🤵⛳👥
No one will care anyway,,,,, 61 No one will care anyway 😂😁😅😉🕐🤪🔉🔞
worth it?,,,,, 62 worth it? 🙌😌😀😊😎😋😁😍
I really thought this will be a hard semester,,,,, 63 I really thought this will be a hard semester 😅😂😢😭💭😘🇦💠
its hard for a schedule to fit all the expectations,,,,, 64 its hard for a schedule to fit all the expectations 😌😁😎🙌😘🔢🔣🔰
dont have enough time for all the sport i want to do,,,,, 65 dont have enough time for all the sport i want to do 😂😅😁😌🤸🔢🔣🚯
all in all i cant imagine how we are able to stay motivated ,,,,, 66 all in all i cant imagine how we are able to stay motivated 😂😅😢😁👤🤵⛳👥
do you prefere star wars or star trek,,,,, 67 do you prefere star wars or star trek 😌🙌😀😊🌟🌠⭐🌃
Mr. Spock is the best!!,,,,, 68 Mr. Spock is the best!! 😌😂😁😅😎😉🤘🤣
I would like to live in the US,,,,, 69 I would like to live in the US 😂😅😢😁👤⛳🤵👥
Studying is so much fun!! ,,,,, 70 Studying is so much fun!! 😂😁😉😅😎😌🙏😀
I dont think so at all ...,,,,, 71 I dont think so at all ... 😂😌😅😁😎🌉🌆📲
i think all the effort will pay off,,,,, 72 i think all the effort will pay off 😂😅😢😁📴🤘🇹🤟
take a flight to ibiza,,,,, 73 take a flight to ibiza 😂😅😢😭😏😘🇦💠
better eating a kebab or a burger,,,,, 74 better eating a kebab or a burger 😂😅😁😢😌😘🇦💠
nothing at all i hate meat,,,,, 75 nothing at all i hate meat 😢😭😅😂🌉🍖🌆🥩
jesus christ!,,,,, 76 jesus christ! 😂😅😁😌😎😉🙌😀
so what do you prefere to eat?,,,,, 77 so what do you prefere to eat? 😂😅😢😁😭🤸🚯🤟
pizza or a different heathy meal,,,,, 78 pizza or a different heathy meal 😂😁😅😌🍕😘🇦💠
"oh dear, you kidding",,,,, 79 oh dear, you kidding 😌😁😎🙌😉😀😂🤟
Donald Trump met Putin outside the USA,,,,, 80 Donald Trump met Putin outside the USA 😂😅😢😭😁😏🤘🤣
Who constructed this bridge,,,,, 81 Who constructed this bridge 😌🙌😁😀😎😊😋😉
I think this church is the largest in town,,,,, 82 I think this church is the largest in town 😁😌😎🙌⛪⛳👥🤵
you have to lost a bet to argue why you have this horrible hair cut,,,,, 83 you have to lost a bet to argue why you have this horrible hair cut 😅😂😢😭🤟🥩👱😘
hopefully we will have wolrd peace in feature,,,,, 84 hopefully we will have wolrd peace in feature 😂😅😁😉👤🤵⛳👥
so we can focus on mor important projects in our world,,,,, 85 so we can focus on mor important projects in our world 😁😌😂😎👥👤🍖⛳
"yes, climate change is real",,,,, 86 yes, climate change is real 😂😅😁😉😢😌😎😏
do you will recommend this nlp lab,,,,, 87 do you will recommend this nlp lab 😁😎😉😌🥼🤸🚯🤟
jonas have to focus on his oral exam tomorrow,,,,, 88 jonas have to focus on his oral exam tomorrow 😌😁😅😂🍖🚩🤣🔛
i wish you all the best,,,,, 89 i wish you all the best 😂😅😁😌🤟🤘🇹🤣
happy bithday darling,,,,, 90 happy bithday darling 😁😌😂😎😅😉🙌😀
i love mixing beer and wine with a shot of tequila,,,,, 91 i love mixing beer and wine with a shot of tequila 😅😂😢😭🏩🍺💌🍷
i love you this much my heart will broke if you leave me,,,,, 92 i love you this much my heart will broke if you leave me 😅😂😢😁🤟💜💟💛
does everybody understand my true feelings,,,,, 93 does everybody understand my true feelings 😂😁😅😉😎😌🙌😀
i think many people will read this and will be confused later,,,,, 94 i think many people will read this and will be confused later 😂😅😁😌🔩🏹🍴🏀
buying a red car will be more expensive,,,,, 95 buying a red car will be more expensive 😂😅😁😉🚃🍎🚋🚓

1 Sentence prediction topic hit sentiment hit both ranked
2 0 Hi how are you? 😁😂😌😎😅😉🙌🤟
3 1 do you've got time 😌😁😎😂🙌🤸🚯🤟
4 2 I go out for party tonight 😂😅😁😌🔰🔢🔣🔤
5 3 I'll take the bus or train 😂😅😢😭🚆🚄🤘🤣
6 4 You look gorgeous in this dress 😌🙌😀😎👗👥👤🤵
7 5 How hard was the exam 😂😅😁😌😎😉🤘🤣
8 6 please can you give me some stuff 😂😅😁😉😎😏🤙🤟
9 7 whats your name 😂😅😁😢😌😎😉📛
10 8 where are you from 😂😅😁😢😌😉😎🤟
11 9 what is your favourite color 😌🙌😀😎😁😊😋😉
12 10 Do you like to play soccer this evening 😅😂😢😭😁😔⚽🤟
13 11 do you have any pets 😂😅😁😢😌🤸🚯🤟
14 12 I watch television all day 😂😅😢😁😉😌😎⌚
15 13 there some fake news but most of the time i dont care 😂😅😁😌🤘🗾🗽💩
16 14 i you fucking kidding 😂😅😢😁🤟🇮🇴🇼
17 15 i we have to hand in our report 😌😁😎🙌✋🤟👊👋
18 16 is the world real 😂😅😁😉😎😌🤘🤣
19 17 i am you father 😂😅😢😭🎅🤟🇴🇼
20 18 is this a true cite 😂😅😁😌😢😘🇦💠
21 19 i like working for my phd 😂😅😢😁🔢🔣🔰🇩
22 20 I at the end of my Master studes 😅😂😢😭🤘🗽🍲🥩
23 21 I like chilling with my friends outside 😂😅😁😉📶🥤💘💝
24 22 are we allowed to extend our presentation time to 35min 😌😁😂😅😎😉🙌🎁
25 23 yes you are because today there no other groups presenting 😌🙌😀😊🎁🚷⛔🚳
26 24 i would love if we needn't write a report 😁😂😌😅💌🏩🤟😘
27 25 no sorry, you have to wirite one. 😢😭😅😔⛔🚳🚷🔞
28 26 ALso Google Docs is not enough, you shell use share latex for your document 😂😅😁😌🐚🔢🔣🔰
29 27 I'll hope we get a good grade 😁😎😌😉😘🇦🙅💠
30 28 I'll really could imagine working in NLP in the feature 😂😅😢😁👤⛳👥🤵
31 29 The weather today is really nice 😂😅😢😭😁😉🤘🤣
32 30 I like to take my dog out for a walk 😅😂😢😭🐕🐶🌭😘
33 31 I am a huge soccer fan 😂😌😁😅⚽😘🇦💠
34 32 I just hate bad tutorials 😢😅😂😭😔😤😁😌
35 33 I am so glad I bought new shoes yesterday 😁😎😌😉🆕🥿👞👠
36 34 My mom likes ice cream 😌😁😎🙌🍨🍦🍧🏒
37 35 This so so much work... 😅😂😢😭😔😁😌😤
38 36 I want to have holidays 😅😂😢😁😭😌😎😉
39 37 Please come to my birthday party 😂😁😌😅😎😉🙌🎂
40 38 why are some people just not replying to emails 😂😅😁😉😎😌😏🚯
41 39 I am sick of studying 😢😅😭😂🗾🧵🧶🥛
42 40 Living in Germany can be expensive 😂😅😢😭👤🤵⛳👥
43 41 I love my new Iphone 😌😎😁😀🆕💌🏩🌑
44 42 Teddy bears are cute 😌🙌😀😁😎😊🐻🧸
45 43 The sun is shining today 😂😅😁😉⛅🌞🤘🤣
46 44 I am really stressed out 😅😢😂😭😔😤😁😏
47 45 Mensa food is disgusting 😂😅😁😌🥫🍲🥘😋
48 46 I am so disappointed of this lecture 😂😅😁😌🗾🧵🧶🥛
49 47 I usually take my bike to work 😅😂😁😌😎😉😢🙌
50 48 This is so sad, I am almost crying 😢😭😅😔😂😤😩😒
51 49 My car broke down yesterday 😅😂😢😭🚋🚓🚃👎
52 50 What is the usual time of study in Germany? 😂😅😢😭🤘🗽🗾🤵
53 51 I try to eat healthy 😂😅😢😁😌😉😎😭
54 52 Seeing people getting good marks with no effort, makes me angry 😂😅😁😢🙅🚷❌🚳
55 53 Live long and prosper 😂😅😢😁🏹🍴🏀🔩
56 54 i love books about wizards 😁😌😎😉📚📘📖📕
57 55 No one understands me 😂😅😁😢🤙🕐🤪🔉
58 56 Why do we even have to study? 😅😂😢😁😭😌🤸🚯
59 57 Tonight I will go drinking 😂😅😢😁😌😉😎🍹
60 58 Lets have a party 😂😅😁😌😎😘🇦💠
61 59 I dont think there is any bias in these sentences 😂😅😁😌👤🤵⛳👥
62 60 I really like to get this freedom in our work 😅😂😢😭👤🤵⛳👥
63 61 No one will care anyway 😂😁😅😉🕐🤪🔉🔞
64 62 worth it? 🙌😌😀😊😎😋😁😍
65 63 I really thought this will be a hard semester 😅😂😢😭💭😘🇦💠
66 64 its hard for a schedule to fit all the expectations 😌😁😎🙌😘🔢🔣🔰
67 65 dont have enough time for all the sport i want to do 😂😅😁😌🤸🔢🔣🚯
68 66 all in all i cant imagine how we are able to stay motivated 😂😅😢😁👤🤵⛳👥
69 67 do you prefere star wars or star trek 😌🙌😀😊🌟🌠⭐🌃
70 68 Mr. Spock is the best!! 😌😂😁😅😎😉🤘🤣
71 69 I would like to live in the US 😂😅😢😁👤⛳🤵👥
72 70 Studying is so much fun!! 😂😁😉😅😎😌🙏😀
73 71 I dont think so at all ... 😂😌😅😁😎🌉🌆📲
74 72 i think all the effort will pay off 😂😅😢😁📴🤘🇹🤟
75 73 take a flight to ibiza 😂😅😢😭😏😘🇦💠
76 74 better eating a kebab or a burger 😂😅😁😢😌😘🇦💠
77 75 nothing at all i hate meat 😢😭😅😂🌉🍖🌆🥩
78 76 jesus christ! 😂😅😁😌😎😉🙌😀
79 77 so what do you prefere to eat? 😂😅😢😁😭🤸🚯🤟
80 78 pizza or a different heathy meal 😂😁😅😌🍕😘🇦💠
81 79 oh dear, you kidding 😌😁😎🙌😉😀😂🤟
82 80 Donald Trump met Putin outside the USA 😂😅😢😭😁😏🤘🤣
83 81 Who constructed this bridge 😌🙌😁😀😎😊😋😉
84 82 I think this church is the largest in town 😁😌😎🙌⛪⛳👥🤵
85 83 you have to lost a bet to argue why you have this horrible hair cut 😅😂😢😭🤟🥩👱😘
86 84 hopefully we will have wolrd peace in feature 😂😅😁😉👤🤵⛳👥
87 85 so we can focus on mor important projects in our world 😁😌😂😎👥👤🍖⛳
88 86 yes, climate change is real 😂😅😁😉😢😌😎😏
89 87 do you will recommend this nlp lab 😁😎😉😌🥼🤸🚯🤟
90 88 jonas have to focus on his oral exam tomorrow 😌😁😅😂🍖🚩🤣🔛
91 89 i wish you all the best 😂😅😁😌🤟🤘🇹🤣
92 90 happy bithday darling 😁😌😂😎😅😉🙌😀
93 91 i love mixing beer and wine with a shot of tequila 😅😂😢😭🏩🍺💌🍷
94 92 i love you this much my heart will broke if you leave me 😅😂😢😁🤟💜💟💛
95 93 does everybody understand my true feelings 😂😁😅😉😎😌🙌😀
96 94 i think many people will read this and will be confused later 😂😅😁😌🔩🏹🍴🏀
97 95 buying a red car will be more expensive 😂😅😁😉🚃🍎🚋🚓

195
Project/Tools/Evaluation_with_csv.ipynb
View File

@ -102,6 +102,9 @@
"#navigation into right path and generating classifier\n", "#navigation into right path and generating classifier\n",
"import sys\n", "import sys\n",
"sys.path.append(\"..\")\n", "sys.path.append(\"..\")\n",
"sys.path.append(\"../naive_approach\")\n",
"\n",
"\n",
"\n", "\n",
"import simple_approach.simple_twitter_learning as stl\n", "import simple_approach.simple_twitter_learning as stl\n",
"clf_advanced = stl.pipeline_manager.load_pipeline_from_files( '../simple_approach/custom_classifier', ['keras_model'], ['vectorizer', 'keras_model'])\n", "clf_advanced = stl.pipeline_manager.load_pipeline_from_files( '../simple_approach/custom_classifier', ['keras_model'], ['vectorizer', 'keras_model'])\n",
@ -143,15 +146,13 @@
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": 5,
"metadata": { "metadata": {},
"collapsed": true
},
"outputs": [], "outputs": [],
"source": [ "source": [
"#sys.path.append(\"..\")\n", "#sys.path.append(\"..\")\n",
"#print(sys.path)\n", "#print(sys.path)\n",
"\n", "\n",
"import naive_approach.naive_approach as clf_naive" "import naive_approach as clf_naive"
] ]
}, },
{ {
@ -248,8 +249,7 @@
" if(current_message != \"\"):\n", " if(current_message != \"\"):\n",
" p = merged_prediction(msg = current_message, target_emojis=top_emojis)\n", " p = merged_prediction(msg = current_message, target_emojis=top_emojis)\n",
"\n", "\n",
" predictions = p\n", " predictions = p"
" update_descriptions()"
] ]
}, },
{ {
@ -265,103 +265,24 @@
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "ename": "ParserError",
"text/html": [ "evalue": "Error tokenizing data. C error: Expected 1 fields in line 27, saw 2\n",
"<div>\n", "output_type": "error",
"<style>\n", "traceback": [
" .dataframe thead tr:only-child th {\n", "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
" text-align: right;\n", "\u001b[0;31mParserError\u001b[0m Traceback (most recent call last)",
" }\n", "\u001b[0;32m<ipython-input-9-7e24563a7fda>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# get table\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpandas\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Evaluation Sentences - Tabellenblatt1.csv\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\n", "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)\u001b[0m\n\u001b[1;32m 653\u001b[0m skip_blank_lines=skip_blank_lines)\n\u001b[1;32m 654\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 655\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 656\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 657\u001b[0m \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
" .dataframe thead th {\n", "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m 409\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 410\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 411\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparser\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 412\u001b[0m \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 413\u001b[0m \u001b[0mparser\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
" text-align: left;\n", "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, nrows)\u001b[0m\n\u001b[1;32m 1003\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'skipfooter not supported for iteration'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1004\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1005\u001b[0;31m \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1006\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1007\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'as_recarray'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
" }\n", "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, nrows)\u001b[0m\n\u001b[1;32m 1746\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnrows\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1747\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1748\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1749\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mStopIteration\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1750\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_first_chunk\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\n", "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.read (pandas/_libs/parsers.c:10862)\u001b[0;34m()\u001b[0m\n",
" .dataframe tbody tr th {\n", "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._read_low_memory (pandas/_libs/parsers.c:11138)\u001b[0;34m()\u001b[0m\n",
" vertical-align: top;\n", "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._read_rows (pandas/_libs/parsers.c:11884)\u001b[0;34m()\u001b[0m\n",
" }\n", "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._tokenize_rows (pandas/_libs/parsers.c:11755)\u001b[0;34m()\u001b[0m\n",
"</style>\n", "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.raise_parser_error (pandas/_libs/parsers.c:28765)\u001b[0;34m()\u001b[0m\n",
"<table border=\"1\" class=\"dataframe\">\n", "\u001b[0;31mParserError\u001b[0m: Error tokenizing data. C error: Expected 1 fields in line 27, saw 2\n"
" <thead>\n", ]
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Sentence</th>\n",
" <th>prediction</th>\n",
" <th>topic hit</th>\n",
" <th>sentiment hit</th>\n",
" <th>both</th>\n",
" <th>ranked</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Hi how are you?</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>do you've got time</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>I go out for party tonight</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>I'll take the bus or train</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>You look gorgeous in this dress</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Sentence prediction topic hit sentiment hit \\\n",
"0 Hi how are you? NaN NaN NaN \n",
"1 do you've got time NaN NaN NaN \n",
"2 I go out for party tonight NaN NaN NaN \n",
"3 I'll take the bus or train NaN NaN NaN \n",
"4 You look gorgeous in this dress NaN NaN NaN \n",
"\n",
" both ranked \n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 NaN NaN \n",
"4 NaN NaN "
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
} }
], ],
"source": [ "source": [
@ -373,48 +294,50 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 11, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [],
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hi how are you?\n"
]
},
{
"ename": "FileNotFoundError",
"evalue": "[Errno 2] No such file or directory: 'word2vec.model'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-11-22a65efd4496>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msentence\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mtrigger_new_prediction\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall_chat\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcurrent_message\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msentence\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 6\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprediction\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m<ipython-input-8-20fe10f899eb>\u001b[0m in \u001b[0;36mtrigger_new_prediction\u001b[0;34m(all_chat, current_message)\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0;31m#merged prediction\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0;32mif\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcurrent_message\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m\"\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 13\u001b[0;31m \u001b[0mp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmerged_prediction\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcurrent_message\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtarget_emojis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtop_emojis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[0mpredictions\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m<ipython-input-7-5ed291336bae>\u001b[0m in \u001b[0;36mmerged_prediction\u001b[0;34m(msg, split, number, target_emojis)\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;31m#predict emojis with the naive approach\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0mprediction_naive\u001b[0m \u001b[0;34m,\u001b[0m \u001b[0mprediction_naive_values\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mclf_naive\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msentence\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlookup\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0mtmp_dict\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnumber_naive\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;31m#filter 0 values\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/GitRepos/NLP-LAB/Project/naive_approach/naive_approach.py\u001b[0m in \u001b[0;36mpredict\u001b[0;34m(sentence, lookup, emojis_to_consider, criteria, lang, n, t)\u001b[0m\n\u001b[1;32m 98\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msentence\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlookup\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0memojis_to_consider\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"all\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcriteria\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"threshold\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlang\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'eng'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.9\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 99\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 100\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mevaluate_sentence\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msentence\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlang\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0memojis_to_consider\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0memojis_to_consider\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 101\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 102\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/GitRepos/NLP-LAB/Project/naive_approach/naive_approach.py\u001b[0m in \u001b[0;36mevaluate_sentence\u001b[0;34m(sentence, description_key, lang, emojis_to_consider, stem)\u001b[0m\n\u001b[1;32m 44\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mevaluate_sentence\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msentence\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdescription_key\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'description'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlang\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'eng'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0memojis_to_consider\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"all\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstem\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 45\u001b[0m \u001b[0;31m# assumes there is a trained w2v model stored in the same directory!\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 46\u001b[0;31m \u001b[0mwv\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKeyedVectors\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"word2vec.model\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmmap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'r'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 47\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 48\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mstem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/gensim/models/keyedvectors.py\u001b[0m in \u001b[0;36mload\u001b[0;34m(cls, fname_or_handle, **kwargs)\u001b[0m\n\u001b[1;32m 120\u001b[0m \u001b[0;34m@\u001b[0m\u001b[0mclassmethod\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 121\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcls\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfname_or_handle\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 122\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mBaseKeyedVectors\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname_or_handle\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 123\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 124\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0msimilarity\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mentity1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mentity2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/gensim/utils.py\u001b[0m in \u001b[0;36mload\u001b[0;34m(cls, fname, mmap)\u001b[0m\n\u001b[1;32m 423\u001b[0m \u001b[0mcompress\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubname\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSaveLoad\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_adapt_by_suffix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 424\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 425\u001b[0;31m \u001b[0mobj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0munpickle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 426\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_load_specials\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmmap\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcompress\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 427\u001b[0m \u001b[0mlogger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"loaded %s\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/gensim/utils.py\u001b[0m in \u001b[0;36munpickle\u001b[0;34m(fname)\u001b[0m\n\u001b[1;32m 1327\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1328\u001b[0m \"\"\"\n\u001b[0;32m-> 1329\u001b[0;31m \u001b[0;32mwith\u001b[0m \u001b[0msmart_open\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'rb'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1330\u001b[0m \u001b[0;31m# Because of loading from S3 load can't be used (missing readline in smart_open)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1331\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mversion_info\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/smart_open/smart_open_lib.py\u001b[0m in \u001b[0;36msmart_open\u001b[0;34m(uri, mode, **kw)\u001b[0m\n\u001b[1;32m 179\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'mode should be a string'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 180\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 181\u001b[0;31m \u001b[0mfobj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_shortcut_open\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0muri\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 182\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mfobj\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 183\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mfobj\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/smart_open/smart_open_lib.py\u001b[0m in \u001b[0;36m_shortcut_open\u001b[0;34m(uri, mode, **kw)\u001b[0m\n\u001b[1;32m 285\u001b[0m \u001b[0mmode\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreplace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'b'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m''\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 286\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 287\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparsed_uri\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0muri_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mopen_kwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 288\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 289\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'word2vec.model'"
]
}
],
"source": [ "source": [
"all_predictions = []\n",
"\n",
"for index, row in df.iterrows():\n", "for index, row in df.iterrows():\n",
" sentence = row[\"Sentence\"]\n", " sentence = row[\"Sentence\"]\n",
" print(sentence)\n", " #print(sentence)\n",
"\n", "\n",
" trigger_new_prediction(all_chat=\"\", current_message = sentence)\n", " trigger_new_prediction(all_chat=\"\", current_message = sentence)\n",
" print(prediction)\n", " #print(predictions)\n",
" \n", " \n",
" #prediction to string\n",
" tmp_prediction = \"\".join(predictions)\n",
" \n",
" #construct the preediction column\n",
" all_predictions.append(tmp_prediction)\n",
" " " "
] ]
}, },
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"df[\"prediction\"] = all_predictions\n",
"\n",
"df.head()\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"df.to_csv(\"Evaluation Sentences - Tabellenblatt1.csv\", sep='\\t', encoding='utf-8')"
]
},
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,

BIN
Project/Tools/Full Emoji space -- positive-negative-plot.png
View File

Binary file not shown.
Side by Side Swipe Overlay

Before

Width:  |  Height:  |  Size: 317 KiB

After

Width:  |  Height:  |  Size: 97 KiB

BIN
Project/Tools/Full Emoji space -- sentiment-plot.png
View File

Binary file not shown.
Side by Side Swipe Overlay

Before

Width:  |  Height:  |  Size: 321 KiB

After

Width:  |  Height:  |  Size: 99 KiB

5
Project/Tools/User_Interface.ipynb
View File

@ -102,6 +102,7 @@
"#navigation into right path and generating classifier\n", "#navigation into right path and generating classifier\n",
"import sys\n", "import sys\n",
"sys.path.append(\"..\")\n", "sys.path.append(\"..\")\n",
"sys.path.append(\"../naive_approach\")\n",
"\n", "\n",
"import simple_approach.simple_twitter_learning as stl\n", "import simple_approach.simple_twitter_learning as stl\n",
"clf_advanced = stl.pipeline_manager.load_pipeline_from_files( '../simple_approach/custom_classifier', ['keras_model'], ['vectorizer', 'keras_model'])\n", "clf_advanced = stl.pipeline_manager.load_pipeline_from_files( '../simple_approach/custom_classifier', ['keras_model'], ['vectorizer', 'keras_model'])\n",
@ -151,7 +152,7 @@
"#sys.path.append(\"..\")\n", "#sys.path.append(\"..\")\n",
"#print(sys.path)\n", "#print(sys.path)\n",
"\n", "\n",
"import naive_approach.naive_approach as clf_naive" "import naive_approach as clf_naive"
] ]
}, },
{ {
@ -557,7 +558,7 @@
{ {
"data": { "data": {
"application/vnd.jupyter.widget-view+json": { "application/vnd.jupyter.widget-view+json": {
"model_id": "6cb4372b3ac5467b8eec0f4cd67f8212", "model_id": "6216e3a271cc4428ba568adbad2fa40c",
"version_major": 2, "version_major": 2,
"version_minor": 0 "version_minor": 0
}, },

107
Project/Tools/emoji_plotting.ipynb
View File

File diff suppressed because one or more lines are too long

BIN
Project/Tools/histogram.png
View File

Binary file not shown.
Side by Side Swipe Overlay

Before

Width:  |  Height:  |  Size: 19 KiB

After

Width:  |  Height:  |  Size: 37 KiB