Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem -Probability, Paradox, and the Reasonable Person Principle +Cross validation +Cluster analysis +Machine learning +Machine learning for healthcare +tf-idf +Boosting (machine learning) +Learning +Gensim +Gradient descent -Pointwise mutual information"

Positive matches

• 0.123 + - Class imbalance
• 0.038 + - word2vec
• 0.036 + - Neural network
• 0.033 + - tfidf
• 0.032 + - Recommender system
• 0.030 + - Neuron
• 0.025 + - Deep learning
• 0.024 + - scikit-learn
• 0.024 + - Data clustering
• 0.024 + - Ulrike von Luxburg
• 0.018 + - Yoav Freund
• 0.018 + - Ron Meir
• 0.018 + - Rob Schapire
• 0.017 + - How to study
• 0.017 + - Michael Ramscar
• 0.016 + - Privacy and Deanonymization
• 0.013 + - NLTK
• 0.013 + - IPython notebook
• 0.011 + - Poker
• 0.011 + - Jupyter/notebook

Negative matches

• 0.028 + - Information theory
• 0.010 + - Lexical feature selection
• 0.005 + - Text analysis
• 0.004 + - Data analysis
• 0.001 + - StanfordNLP
• 0.001 + - NLP
• 0.001 + - CNN
• 0.001 + - Long short-term memory
• 0.001 + - Dialog act
• 0.001 + - KenLM
• 0.001 + - fastText
• 0.001 + - Latent Dirichlet allocation
• 0.001 + - Sentiment analysis
• 0.001 + - Word segmentation
• 0.000 + - Kyunghyun Cho
• 0.000 + - spaCy
• 0.000 + - Convolutional neural network
• 0.000 + - Word embedding
• 0.000 + - IPython