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) -Rob Schapire -Data clustering +Yoav Freund -Pointwise mutual information"

Positive matches

• 0.124 + - Class imbalance
• 0.034 + - Gradient descent
• 0.027 + - Recommender system
• 0.024 + - Ulrike von Luxburg
• 0.022 + - scikit-learn
• 0.018 + - Ron Meir
• 0.016 + - Learning
• 0.014 + - tfidf
• 0.014 + - Regular expression
• 0.013 + - Gensim
• 0.013 + - NLTK
• 0.012 + - IPython notebook
• 0.011 + - Poker
• 0.011 + - Jupyter/notebook
• 0.011 + - Future of work
• 0.011 + - Regex
• 0.010 + - Privacy and Deanonymization
• 0.008 + - Neural network
• 0.007 + - Random forest
• 0.006 + - Decision tree

Negative matches

• 0.028 + - Information theory
• 0.020 + - Lexical feature selection
• 0.018 + - Text analysis
• 0.001 + - Convolutional neural network
• 0.001 + - StanfordNLP
• 0.001 + - NLP
• 0.000 + - scispaCy
• 0.000 + - Recurrent neural network
• 0.000 + - Sentence embedding
• 0.000 + - KenLM
• 0.000 + - Topic modeling
• 0.000 + - Cross entropy
• 0.000 + - Kullback–Leibler divergence
• 0.000 + - Data analysis
• 0.000 + - BookNLP
• 0.000 + - KoNLPy
• 0.000 + - Tomas Mikolov
• 0.000 + - Biomedical natural language processing
• 0.000 + - fastText
• 0.000 + - Information Theory, Inference, and Learning Algorithms