Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem -Probability, Paradox, and the Reasonable Person Principle +Cross validation +Cluster analysis +Computer science -Ulrike von Luxburg +Class imbalance +scikit-learn +tf-idf -Data clustering +Lexical feature selection -NLTK"

Positive matches

• 0.215 + - Machine learning
• 0.044 + - Text analysis
• 0.032 + - Pointwise mutual information
• 0.026 + - Data analysis
• 0.023 + - Gradient descent
• 0.021 + - Decision tree
• 0.020 + - Recommender system
• 0.016 + - Random forest
• 0.015 + - Gensim
• 0.012 + - Jupyter/notebook
• 0.011 + - Python/Modules
• 0.011 + - Python
• 0.011 + - Poker
• 0.011 + - IPython notebook
• 0.011 + - skorch
• 0.011 + - Tim Hopper
• 0.010 + - Deep learning
• 0.010 + - Bookshelf
• 0.009 + - Boosting (machine learning)
• 0.008 + - Interdisciplinary research

Negative matches

• 0.008 + - Natural language processing
• 0.001 + - Paper/Gatys2015
• 0.001 + - scispaCy
• 0.001 + - Convolutional neural network
• 0.001 + - Musical composition
• 0.000 + - spaCy
• 0.000 + - Brain and deep learning
• 0.000 + - Amazon Elastic Compute Cloud
• 0.000 + - Neural network
• 0.000 + - RNN
• 0.000 + - Residual Learning
• 0.000 + - Long short-term memory
• 0.000 + - Residual leanrning
• 0.000 + - Attention (Deep learning)