Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem +Machine learning -Information theory"

Positive matches

• 0.196 + - Class imbalance
• 0.064 + - Paradox
• 0.051 + - Probability
• 0.032 + - Jupyter/notebook
• 0.030 + - IPython notebook
• 0.028 + - Poker
• 0.028 + - Probability, Paradox, and the Reasonable Person Principle
• 0.016 + - Recommender system
• 0.015 + - Gradient descent
• 0.014 + - Learning
• 0.011 + - Future of work
• 0.010 + - Tom M. MItchell
• 0.010 + - Cluster analysis
• 0.010 + - Weka
• 0.010 + - Carlos Guestrin
• 0.010 + - Training dataset
• 0.010 + - One-shot learning
• 0.010 + - Michael I. Jordan
• 0.010 + - Python#Modules_.26_Libraries
• 0.010 + - Boosting (machine learning)

Negative matches

• 0.115 + - Lexical feature selection
• 0.021 + - Kullback–Leibler divergence
• 0.021 + - Information Theory, Inference, and Learning Algorithms
• 0.021 + - Cross entropy
• 0.021 + - Pointwise mutual information
• 0.021 + - Gibbs' inequality
• 0.018 + - David Feldman
• 0.018 + - David MacKay
• 0.012 + - Text analysis
• 0.002 + - Data analysis
• 0.001 + - Biomedical natural language processing
• 0.001 + - Liquid state machine
• 0.001 + - NLP
• 0.001 + - Residual leanrning
• 0.000 + - Convolutional neural network
• 0.000 + - Pathogen transmission
• 0.000 + - Neural doodle
• 0.000 + - spaCy
• 0.000 + - Neuron
• 0.000 + - tfidf