Dirty secret of machine learning: Hyper-parameters
{"Image DocumentName": "Dirty secret of machine learning: Hyper-parameters", "Image ImageDescription": "Hyper-parameters: settings of a learning algorithm. Tree ensembles (boosting, random forest): #trees, #leaves, learning rate, \u2026 Linear models (perceptron, SVM): regularization, learning rate, \u2026 Neural networks: #hidden units, #layers, learning rate, momentum, \u2026 Hyper-parameters can make a difference in learned model accuracy. Example: AUC of boosted trees. on Census dataset (income prediction)", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}