How can Machine Learning apply to insurance
{"Image DocumentName": "How can Machine Learning apply to insurance?", "Image ImageDescription": "Basic Approach of Decision Trees. Data split based on some target and criterion. Target: entropy, frequency, severity, loss ratio, loss cost, etc. Criteria: maximize the difference, maximize the Gini coefficient, minimize the entropy, etc. Each path is split again until some ending criterion is met. Statistical tests on the utility of further splitting. No further improvement possible. Others. The tree may be include some pruning criteria. Performance on a validation set of data (i.e. reduced error pruning) Rule post-pruning. Number of Units. 1. >1. Cov Limit. <=10k. >10k. Number of Insured. 1,2. >2.", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}