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 +word2vec -Graph embedding"

Positive matches

• 0.116 + - Class imbalance
• 0.035 + - Neural network
• 0.032 + - Neuron
• 0.031 + - tfidf
• 0.028 + - Text analysis
• 0.027 + - Recommender system
• 0.025 + - Deep learning
• 0.022 + - Data clustering
• 0.022 + - Ulrike von Luxburg
• 0.021 + - scikit-learn
• 0.020 + - Pointwise mutual information
• 0.020 + - Lexical feature selection
• 0.017 + - Ron Meir
• 0.017 + - Yoav Freund
• 0.016 + - How to study
• 0.016 + - Michael Ramscar
• 0.016 + - Rob Schapire
• 0.013 + - Regular expression
• 0.013 + - Future of work
• 0.013 + - NLTK

Negative matches

• 0.016 + - GraphSAGE
• 0.016 + - PyTorch-BigGraph
• 0.012 + - Continuous embedding
• 0.007 + - Network geometry
• 0.003 + - Probability
• 0.001 + - Paper/Tshitoyan2019unsupervised
• 0.001 + - Science of science
• 0.001 + - Topic model
• 0.000 + - Twitter
• 0.000 + - Leigh Weston
• 0.000 + - NMF
• 0.000 + - Ziqin Rong
• 0.000 + - Embedded topic model
• 0.000 + - Natural language processing
• 0.000 + - Hierarchical softmax
• 0.000 + - Paper