1. 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

2. 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

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

4. 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.