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) +NLTK +Pointwise mutual information +Poker +scikit-learn -Ron Meir -Text analysis"

Positive matches

• 0.118 + - Class imbalance
• 0.047 + - tfidf
• 0.033 + - Natural language processing
• 0.032 + - Information theory
• 0.030 + - Lexical feature selection
• 0.028 + - Gradient descent
• 0.027 + - Recommender system
• 0.021 + - Data clustering
• 0.021 + - Ulrike von Luxburg
• 0.021 + - Learning
• 0.016 + - Rob Schapire
• 0.016 + - Regular expression
• 0.016 + - Yoav Freund
• 0.015 + - Random forest
• 0.013 + - Decision tree
• 0.012 + - Gensim
• 0.011 + - Python/Modules
• 0.011 + - Jupyter/notebook
• 0.010 + - Tim Hopper
• 0.010 + - Python

Negative matches

• 0.022 + - Data analysis
• 0.019 + - Science
• 0.010 + - Interdisciplinary research
• 0.005 + - Industry-Academic Partnership
• 0.003 + - Science policy
• 0.001 + - Policy
• 0.001 + - Software engineering in research
• 0.001 + - Collaborative software
• 0.001 + - fastText
• 0.001 + - Topic modeling
• 0.001 + - Kyunghyun Cho
• 0.001 + - KoNLPy
• 0.000 + - Sentence embedding
• 0.000 + - Sentiment analysis
• 0.000 + - KenLM
• 0.000 + - String metric
• 0.000 + - Dialog act
• 0.000 + - Word segmentation