Gratka flats challenge

Predict the price of flats in Poznań. Each entry in training data set is described by: Price, Rooms, SqrMeters, Floor, Location, Description. Evaluation metric is RMSE. [ver. 1.0.0]

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[anonymised]   2019-03-19 13:12
submitted a solution:test commit
[anonymised]   2019-03-19 13:11
submitted a solution:test commit
[anonymised]   2019-03-05 12:55
submitted a solution:testtest
[anonymised]   2019-02-26 14:12
submitted a solution:test commit
[anonymised]   2017-12-17 22:54
submitted a solution:Zadniae
[anonymised]   2017-12-17 09:28
submitted a solution:Wykonane
[anonymised]   2017-12-15 22:05
submitted a solution:UMZ-2017-zaoczne-004 gradient descent
[anonymised]   2017-12-13 22:34
submitted a solution:Zadanie 004 z kodem programu
[anonymised]   2017-12-13 22:30
submitted a solution:gradient prosty
kubapok   2017-10-06 09:13
submitted a solution:mean
Paweł Skórzewski   2017-09-30 17:59
submitted a solution:Naive linear regression
p/tlen   2017-09-30 15:34
submitted a solution:dsdsd
p/tlen   2017-09-28 20:22
submitted a solution:23
p/tlen   2017-09-28 20:15
submitted a solution:22
p/tlen   2017-09-28 19:24
submitted a solution:wersja 2100
p/tlen   2017-09-28 19:23
submitted a solution:wersja 2000
[anonymised]   2016-12-12 20:09
submitted a solution:M^2 regresja liniowa
[anonymised]   2016-12-12 11:14
submitted a solution:chyze szynszyle: mean estimator
[anonymised]   2016-12-12 10:12
submitted a solution:chyze szynszyle: ostatni raz k-nn
[anonymised]   2016-12-12 10:10
submitted a solution:chyze szynszyle: ostatni raz random forest
[anonymised]   2016-12-12 00:26
submitted a solution:one more try
[anonymised]   2016-12-12 00:09
submitted a solution:chyze szynszyle: linear model
[anonymised]   2016-12-12 00:07
submitted a solution:Foki: wynik v2
[anonymised]   2016-12-11 23:44
submitted a solution:one more try
[anonymised]   2016-12-11 23:38
submitted a solution:one more try
[anonymised]   2016-12-11 23:35
submitted a solution:one more try
[anonymised]   2016-12-11 23:35
submitted a solution:chyze szynszyle: bez normalizacji na dzielnicach
[anonymised]   2016-12-11 23:34
submitted a solution:chyze szynszyle: k-nn, dodanie nowych cech
[anonymised]   2016-12-11 23:29
submitted a solution:Foki: wyniki
[anonymised]   2016-12-11 23:28
submitted a solution:chyze szynszyle: k-nn bez normalizacji danych, hehe
[anonymised]   2016-12-11 23:24
submitted a solution:chyze szynszyle: k-nn, wszystkie cechy
[anonymised]   2016-12-11 23:22
submitted a solution:chyze szynszyle: jeszcze więcej słów w bag of words
[anonymised]   2016-12-11 23:14
submitted a solution:chyze szynszyle: ostatni krzyk szynszyli
[anonymised]   2016-12-11 23:12
submitted a solution:testoza
[anonymised]   2016-12-11 23:11
submitted a solution:chyze szynszyle: bez usuwania outliers
[anonymised]   2016-12-11 23:10
submitted a solution:chyze szynszyle: nie pamiętam co zmieniłem
[anonymised]   2016-12-11 23:09
submitted a solution:testoza
[anonymised]   2016-12-11 23:06
submitted a solution:chyze szynszyle: k-nn using bag of words, more words, more train data
[anonymised]   2016-12-11 23:04
submitted a solution:chyze szynszyle: k-nn using all features and bag of words, more train data
[anonymised]   2016-12-11 23:02
submitted a solution:Foki: prace nad wynikiem
[anonymised]   2016-12-11 22:59
submitted a solution:chyze szynszyle: k-nn using bag of words, less words
[anonymised]   2016-12-11 22:58
submitted a solution:chyze szynszyle: k-nn using all features and bag of words
[anonymised]   2016-12-11 22:56
submitted a solution:chyze szynszyle: k-nn using bag of words, more words
[anonymised]   2016-12-11 22:53
submitted a solution:chyze szynszyle: k-nn using bag of words
[anonymised]   2016-12-11 22:53
submitted a solution:Foki: wyjście
[anonymised]   2016-12-11 22:52
submitted a solution:chyze szynszyle: regresja liniowa usuniete dane odstajace
[anonymised]   2016-12-11 22:50
submitted a solution:chyze szynszyle: random forest
[anonymised]   2016-12-11 22:31
submitted a solution:Foki: liczba wyników
[anonymised]   2016-12-11 22:27
submitted a solution:Foki: prace nad wynikiem
[anonymised]   2016-12-11 22:23
submitted a solution:Foki: konwertowanie
[anonymised]   2016-12-11 22:07
submitted a solution:Foki: testowanie zbioru
[anonymised]   2016-12-11 21:37
submitted a solution:Foki: zapis do pliku
[anonymised]   2016-12-11 21:35
submitted a solution:Foki: zapis do pliku
[anonymised]   2016-12-11 21:33
submitted a solution:zpd: En final
[anonymised]   2016-12-11 20:47
submitted a solution:darkside: Lr + 1 additional feature
[anonymised]   2016-12-11 20:39
submitted a solution:LR with other feature
[anonymised]   2016-12-11 20:32
submitted a solution:chyże szynszyle: k-nn add new feature
[anonymised]   2016-12-11 20:31
submitted a solution:LR + 1 feature
[anonymised]   2016-12-11 20:26
submitted a solution:Foki: pierwsze przymiarki
[anonymised]   2016-12-11 19:54
submitted a solution:chyże szynszyle: k-nn, add more train examples
[anonymised]   2016-12-11 19:30
submitted a solution:chyze szynszyle: regresja liniowa glm
[anonymised]   2016-12-11 19:08
submitted a solution:LR + 2 new features
[anonymised]   2016-12-11 18:02
submitted a solution:test
[anonymised]   2016-12-11 17:54
submitted a solution:chyze szynszyle: regresja liniowa
[anonymised]   2016-12-11 17:47
submitted a solution:chyze szynszyle: regresja liniowa
[anonymised]   2016-12-11 17:33
submitted a solution:test
[anonymised]   2016-12-11 17:18
submitted a solution:mean
[anonymised]   2016-12-11 16:43
submitted a solution:test
[anonymised]   2016-12-11 16:38
submitted a solution:test
[anonymised]   2016-12-11 16:37
submitted a solution:test
[anonymised]   2016-12-11 16:07
submitted a solution:test
[anonymised]   2016-12-11 14:40
submitted a solution:chyze_szynszyle: solution using svm
[anonymised]   2016-12-11 14:34
submitted a solution:chyze szynszyle: first solution using k-NN
[anonymised]   2016-12-11 12:30
submitted a solution:En3 + new feature
[anonymised]   2016-12-11 02:20
submitted a solution:linear model, fixed bug
[anonymised]   2016-12-10 19:56
submitted a solution:LR no1
[anonymised]   2016-12-10 19:25
submitted a solution:LR
[anonymised]   2016-12-10 16:31
submitted a solution:words counting
[anonymised]   2016-12-10 12:52
submitted a solution:En3
[anonymised]   2016-12-10 12:31
submitted a solution:En2
[anonymised]   2016-12-10 12:27
submitted a solution:En1
[anonymised]   2016-12-10 12:21
submitted a solution:En1
[anonymised]   2016-12-10 12:00
submitted a solution:LR + multi
[anonymised]   2016-12-10 11:48
submitted a solution:LR + 2 new features
[anonymised]   2016-12-09 22:42
submitted a solution:submission
[anonymised]   2016-12-09 20:48
submitted a solution:
[anonymised]   2016-12-09 20:39
submitted a solution:submission
[anonymised]   2016-12-09 17:39
submitted a solution:MLP + new feature
[anonymised]   2016-12-09 17:31
submitted a solution:MLP
[anonymised]   2016-12-09 17:27
submitted a solution:SVR
[anonymised]   2016-12-09 17:15
submitted a solution:LR + new feature (no noise)
[anonymised]   2016-12-09 17:05
submitted a solution:LR + new feature
[anonymised]   2016-12-09 16:49
submitted a solution:MLP
[anonymised]   2016-12-08 21:59
submitted a solution:LR2
[anonymised]   2016-12-08 21:52
submitted a solution:LR
[anonymised]   2016-12-08 21:26
submitted a solution:test5
[anonymised]   2016-12-08 16:48
submitted a solution:test4
[anonymised]   2016-12-08 16:06
submitted a solution:test3
[anonymised]   2016-12-08 15:55
submitted a solution:test2
[anonymised]   2016-12-08 15:40
submitted a solution:test
[anonymised]   2016-12-08 12:04
submitted a solution:LP
[anonymised]   2016-12-07 17:21
submitted a solution:falstart
[anonymised]   2016-12-07 17:10
submitted a solution:first submission
[anonymised]   2016-12-07 16:25
submitted a solution:code, no data
[anonymised]   2016-12-06 05:26
submitted a solution:experiment
[anonymised]   2016-12-06 04:11
submitted a solution:test
[anonymised]   2016-12-06 01:52
submitted a solution:test
[anonymised]   2016-12-06 00:52
submitted a solution:random experiment
[anonymised]   2016-12-06 00:49
submitted a solution:random experiment
[anonymised]   2016-12-06 00:20
submitted a solution:test
[anonymised]   2016-12-05 23:50
submitted a solution:test
[anonymised]   2016-12-05 23:42
submitted a solution:test
[anonymised]   2016-12-05 22:43
submitted a solution:test 3
[anonymised]   2016-12-05 22:39
submitted a solution:test 2
[anonymised]   2016-12-05 22:37
submitted a solution:test 1
[anonymised]   2016-12-05 22:26
submitted a solution:trivial linear model
[anonymised]   2016-12-05 22:18
submitted a solution:first test, poor solution
[anonymised]   2016-12-04 17:23
submitted a solution:even closer to mean + 510
[anonymised]   2016-12-04 17:15
submitted a solution:even closer to mean
[anonymised]   2016-12-04 16:56
submitted a solution:simple solution, closer to mean
[anonymised]   2016-12-04 16:40
submitted a solution:simple solution, rm only
[anonymised]   2016-12-04 16:36
submitted a solution:simple solution, mtr only
[anonymised]   2016-12-04 16:31
submitted a solution:simple solution, mtr+fltTp
[anonymised]   2016-12-04 16:22
submitted a solution:simple solution, warm start
[anonymised]   2016-12-04 16:18
submitted a solution:simple solution, learningRate = optimal
[anonymised]   2016-12-04 16:13
submitted a solution:simple solution, learningRate = constant
[anonymised]   2016-12-04 16:10
submitted a solution:simple solution, power_t = 0.7
[anonymised]   2016-12-04 16:03
submitted a solution:simple solution, penalty = elastic net
[anonymised]   2016-12-04 15:58
submitted a solution:simple solution, penalty = l1
[anonymised]   2016-12-04 15:50
submitted a solution:simple solution, penalty = l2
[anonymised]   2016-12-04 15:44
submitted a solution:simple solution, loss method = eps_ins_sqr
[anonymised]   2016-12-04 15:38
submitted a solution:simple solution, loss method = eps_insens
[anonymised]   2016-12-04 15:30
submitted a solution:simple solution, loss method = huber
[anonymised]   2016-12-04 15:23
submitted a solution:simple solution, l1=0.8
[anonymised]   2016-12-04 14:38
submitted a solution:simple solution, l1=0.4
[anonymised]   2016-12-04 14:09
submitted a solution:simple solution, but more epochs
[anonymised]   2016-12-04 13:38
submitted a solution:simple solution
[anonymised]   2016-12-04 13:28
submitted a solution:Also mean, but better
[anonymised]   2016-12-03 21:15
submitted a solution:Klol
[anonymised]   2016-12-03 21:15
submitted a solution:Klol
[anonymised]   2016-12-03 20:51
submitted a solution:idk
[anonymised]   2016-12-03 20:18
submitted a solution:0.1kmr
[anonymised]   2016-12-03 19:52
submitted a solution:nowy regresor
[anonymised]   2016-12-03 00:48
submitted a solution:bigger lower
[anonymised]   2016-12-03 00:45
submitted a solution:stupid RMSE prediction * p
[anonymised]   2016-12-03 00:42
submitted a solution:stupid RMSE prediction * 1,36
[anonymised]   2016-12-03 00:36
submitted a solution:stupid RMSE prediction * 1,36
[anonymised]   2016-12-03 00:35
submitted a solution:stupid RMSE prediction
[anonymised]   2016-12-03 00:33
submitted a solution:stupid RMSE prediction
[anonymised]   2016-12-03 00:32
submitted a solution:stupid RMSE prediction
[anonymised]   2016-12-03 00:03
submitted a solution:xxx
[anonymised]   2016-12-03 00:02
submitted a solution:xxx
[anonymised]   2016-12-03 00:02
submitted a solution:xxx
[anonymised]   2016-12-02 23:59
submitted a solution:xxx
[anonymised]   2016-12-02 23:41
submitted a solution:xxx
[anonymised]   2016-12-02 23:40
submitted a solution:xxx
[anonymised]   2016-12-02 23:35
submitted a solution:xxx
[anonymised]   2016-12-02 23:31
submitted a solution:xxx
[anonymised]   2016-12-02 23:30
submitted a solution:xxx
[anonymised]   2016-12-02 23:30
submitted a solution:xxx
[anonymised]   2016-12-02 23:26
submitted a solution:means increased
[anonymised]   2016-12-02 23:25
submitted a solution:means increased
[anonymised]   2016-12-02 23:24
submitted a solution:means increased
[anonymised]   2016-12-02 23:23
submitted a solution:means increased
[anonymised]   2016-12-02 23:22
submitted a solution:means increased
[anonymised]   2016-12-02 23:05
submitted a solution:means unfiltered
[anonymised]   2016-12-02 23:01
submitted a solution:at_least_means
[anonymised]   2016-12-01 19:22
submitted a solution:at_least_we_tried team first solution
[anonymised]   2016-11-23 21:24
submitted a solution:Instance Monad Siekiera - Vowpal Wabbit with options --passes 500 --ngram 2 -b 20 --l1 0.0000001 --l2 0.0000001 --nn 10 --cubic mld
[anonymised]   2016-11-23 13:05
submitted a solution:VW with NN, ngrams = 3, passes = 100
[anonymised]   2016-11-23 11:12
submitted a solution:pitu pitu
[anonymised]   2016-11-16 09:36
submitted a solution:admin: always mean price