grid-search
- Hyperparameter optimization across multiple models in scikit-learn (23 Feb 2018)
This blog post shows how to perform hyperparameter optimization across multiple models in scikit-learn, using a helper class one can tune several models at once and print a report with the results and parameters settings.
viterbi sequence-prediction pos-tags neural-networks word2vec scikit-learn conditional-random-fields NER word-embeddings syntactic-dependencies reference-post gensim fasttext evaluation_metrics document-classification classification SyntaxNet NLTK LSTM wikidata tokenization tf-idf stanford-NER sparql seq2seq relationship-extraction recurrent-neural-networks portuguese pandas nlp named-entity-recognition naive-bayes multi-label-classification maximum-entropy-markov-models machine-translation logistic-regression language-models information-extraction imbalanced_data hyperparameter-optimization hidden-markov-models grid-search glove embeddings doc2vec dependency-graph deep-learning data-challenge convolutional-neural-networks conference cheat-sheet character-language-models character-embeddings attention RNN PyData KOVENS GRU ELMo BERT