Tags

tag description
2-dimensional classifier or regression on two variables
algo non-trivial algorithm implemented
analysis some extra analysis done, not just giving the test results
bagging bagging/bootstraping used
bernoulli Bernoulli (naive Bayes) model used
better-than-no-model-baseline significantly better than stupid, no-model baseline (e.g. returning the majority class)
bigram bigrams considered
c++ written (partially or fully) in C++
char-n-grams character n-grams
chi-square chi-square test used
cnn Convolutional Neural Network
crm-114 CRM-114 used
decision-tree decision tree used
fasttext fasttext used
feature-engineering used more advanced pre-processing, feature engineering etc.
haskell written (partially or fully) in Haskell
java written (partially or fully) in Java
kenlm KenLM used
k-means k-means or its variant used
knn k nearest neighbors
knowledge-based some external source of knowledge used
lemmatization lemmatization used
linear-regression linear regression used
lisp written (partially or fully) in Lisp
lm a language model used
logistic-regression logistic regression used
lstm LSTM network
mert MERT (or equivalent) for Moses
moses Moses MT
multidimensional classifier or regression on many variables
multinomial multinomial (naive Bayes) model used
naive-bayes Naive Bayes Classifier used
neural-network neural network used
new-leader significantly better than the current top result
n-grams n-grams used
no-model-baseline significantly better than stupid, no-model baseline (e.g. returning the majority class)
null-model null model baseline
perl written (partially or fully) in Perl
python written (partially or fully) in Python 2/3
r written (partially or fully) in R
random-forest Random Forest used
ready-made Machine Learning framework/library/toolkit used, algorithm was not implemented by the submitter
regexp handcrafted regular expressions used
regularization some regularization used
rnn Recurrent Neural Network
ruby written (partially or fully) in Ruby
scala written (partially or fully) in Scala
scikit-learn sci-kit learn used
self-made algorithm implemented by the submitter, no framework used
stemming stemming used
stupid simple, stupid rule-based solution
temporal temporal information taken into account
tf-idf tf-idf used
trigram trigrams considered
unigram only unigrams considered
vowpal-wabbit Vowpal Wabbit used
word2vec Word2Vec
wordnet some wordnet used
xgboost xgboost used