mvn clean package
java -jar <jar-with-dependencies> param1 param2 param3 param4 param5
* <percentage of training set (integer 1-99)>
* <k for kNN (integer >0)>
* <number of keywords (integer >0)>
* <numerical metric [eucl|manh|cheb]>
* <text metric [trigram|tfm]>
* "1",
* "2,0-50", "2,50-100",
* "3,0-50,tfidf",
* "3,50-100,tfidf",
* "3,0-50,tfcitfoc",
* "3,50-100,tfcitfoc",
* "4,0-50,tfidf",
* "4,50-100,tfidf",
* "4,0-50,tfcitfoc",
* "4,50-100,tfcitfoc",
* "5,0-50,tfidf",
* "5,50-100,tfidf",
* "5,0-50,tfcitfoc",
* "5,50-100,tfcitfoc",
* "6,0-50,tfidf",
* "6,50-100,tfidf",
* "6,0-50,tfcitfoc",
* "6,50-100,tfcitfoc",
Uncomment selected function in main function in main.py and run by python main.py
The rest of information is stored in script
- Install PostgreSQL with JDBC Driver
- Create database
ksr_fuzzymanually or by using python script in sql-script directory - Build JAR -
mvn clean packageand the runjava -jar $JAR_NAME$ -spto read data from csv file and save them into ksr_fuzzy database or restore database fromdata-dump.sqlfile after that runjava -jar $JAR_NAME$ -slto create and seed tables for labelWrapper and LinguisticQuantifierWrapper
- Install and create database
ksr_fuzzyotherwise application with fail to start or comment out whole application.properties file - h2 database will be used
- Single param -
seed_pollutionor-spto seed database from csv file - Single param -
seed_linguisticor-slto seed database with linguistic data
filter_data.py- filtering csv data - removes rows with NaN values, removes selected columnsmain.py- script with experiments for reportmerge_generated_summary.py- merging results frommain.pyremove_poor_summary.py- removing merged results frommerge_generated_summary.pywhen T1 is below passed valuedraw_chart.py- generating chart for Quantifiergenerate_function.py- generating membership function formulasgenerate_function_to_file.py- usage ofgenerate_function.pywith selected paramsdata-dump- script with dumped data from database after filtering - restore->custom or tar and filename dump-data
select no2aqi, date_local
from pollution
where date_part('month', date_local)>=6
and date_part('month', date_local)<=9
order by no2aqi desc


