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Positive matches

• 0.055 + - Machine learning
• 0.033 + - IPython notebook
• 0.032 + - Computational social science
• 0.024 + - Probability theory
• 0.024 + - Probability distribution
• 0.023 + - Travelling salesman problem
• 0.014 + - IPython
• 0.014 + - Jupyter
• 0.014 + - Industry-Academic Partnership
• 0.011 + - Interdisciplinary research
• 0.011 + - Gradient descent
• 0.010 + - SSH tunneling
• 0.008 + - Big data
• 0.008 + - Trey Causey
• 0.008 + - Data
• 0.008 + - Science
• 0.008 + - John Hopcroft
• 0.007 + - SSH
• 0.004 + - Science policy
• 0.003 + - Learning

Negative matches

• 0.029 + - Class imbalance problem
• 0.002 + - EM algorithm
• 0.002 + - Dimensionality reduction
• 0.001 + - D3
• 0.001 + - Random forest
• 0.001 + - Naive Bayes classifier
• 0.001 + - Carlos Guestrin
• 0.001 + - Information theory
• 0.001 + - Cluster analysis
• 0.001 + - Image completion
• 0.001 + - Machine learning for healthcare
• 0.001 + - Sargur Srihari
• 0.001 + - Cross validation
• 0.001 + - Stability selection
• 0.000 + - Python#Modules_.26_Libraries
• 0.000 + - Decision tree
• 0.000 + - Artificial neural network
• 0.000 + - Michael I. Jordan
• 0.000 + - GraphLab
• 0.000 + - Tom M. MItchell