Auto Coding System Development and application of a simple machine learning algorithm for multiclass classifications Yukako Toko, Toshiyuki Shimono, Kazumi Wada National Statistics Center, Japan NTTS2017 in Brussels, 15 March 2017 Proposal Auto Coding System multiclass classification, more than 570 classes Purpose free format, mostly less than 5 words Data set “The Family Income and Expenditure Survey” Apply to

Learning Classifying Methods Training data set NLP Feature freq. table A simple machine learning algorithm for multiclass classifications Learning Training data set NLP Feature freq. table Input Output NLP Class Pick-out Confidence Calc. Classifying NLP: Natural Language Processing

Results Accuracy vs Coverage Accuracy % Coverage % A simple machine learning algorithm for multiclass classifications Accuracy vs Coverage Accuracy % Coverage %

High accuracy with the majority of data Summary A simple machine learning algorithm for multiclass classifications High accuracy with the majority of data 99% with 67%. 98% with 80%. 91% as a whole Quick processing Learning/Classifying for 1,000,000 : < 6min. Simple algorithm Applicable to various classification systems Thank you for your attention.