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) +Recommender system +Netflix prize -Pointwise mutual information"

Positive matches

• 0.150 + - Class imbalance
• 0.035 + - Gradient descent
• 0.026 + - Data clustering
• 0.026 + - Ulrike von Luxburg
• 0.024 + - scikit-learn
• 0.020 + - Learning
• 0.020 + - Rob Schapire
• 0.020 + - Yoav Freund
• 0.020 + - Ron Meir
• 0.018 + - Future of work
• 0.018 + - Privacy and Deanonymization
• 0.014 + - tfidf
• 0.013 + - Gensim
• 0.013 + - NLTK
• 0.012 + - Poker
• 0.012 + - Jupyter/notebook
• 0.012 + - IPython notebook
• 0.011 + - Regular expression
• 0.009 + - Regex
• 0.008 + - Decision tree

Negative matches

• 0.030 + - Information theory
• 0.021 + - Lexical feature selection
• 0.012 + - Text analysis
• 0.003 + - Data analysis
• 0.003 + - Probability
• 0.001 + - StanfordNLP
• 0.001 + - Kyunghyun Cho
• 0.001 + - Word embedding
• 0.001 + - NLP
• 0.001 + - spaCy
• 0.000 + - fastText
• 0.000 + - KenLM
• 0.000 + - Amazon Elastic Compute Cloud
• 0.000 + - Sentiment analysis
• 0.000 + - Kullback–Leibler divergence
• 0.000 + - CNN
• 0.000 + - Sentence embedding
• 0.000 + - Information Theory, Inference, and Learning Algorithms
• 0.000 + - Cross entropy