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Text classifier 2

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Advanced neural network based on https://github.com/RusZ/TextClassifier

TODO

  • Mention about DDD paradygme in description
  • Transfer network learning to Apache Ignite platform or S3 Cloud

Text Classifier

Application for text classification using neural networks.

Requirements

  • Java SE Development Kit 8 (jdk-1.8)

Dependencies

  • Encog Machine Learning Framework (org.encog:encog-core:3.3.0)
  • Apache POI (org.apache.poi:poi-ooxml:3.16)
  • SQLiteJDBC (org.xerial:sqlite-jdbc:3.19.3)
  • JUnit (junit:junit:4.12)
  • H2 Database Engine (com.h2database:h2:1.4.196)
  • Mockito (org.mockito:mockito-core:2.8.47)
  • Hibernate ORM (org.hibernate:hibernate-core:5.2.10.Final, org.hibernate:hibernate-entitymanager:5.2.10.Final)
  • SLF4J (org.slf4j:slf4j-log4j12:1.7.25)
  • Javassist (org.javassist:javassist:3.22.0-CR2)

Config.ini file description

Parameter Description Possible values
db_path Path for database files and trained classifiers Example: ./db
dao_type Method of data storage and access jdbc, hibernate
dbms_type Database management system sqlite, h2
db_filename Database name Example: TextClassifier
ngram_strategy Text splitting algorithm unigram, filtered_unigram, bigram, filtered_bigram

Quick start guide

  1. When you launch application first time, it will ask you for XLSX-file with data for training. The file can include one or two sheets. First sheet should contain data for training, second sheet should contain data for testing of accurancy. File structure:

  1. After that application will build vocabulary, will create and train neural network for each Characteristic.
  2. Restart application and use it for text classification.

Author

License

This project is licensed under the MIT License - see the LICENSE file for details.

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Advanced neural network based on https://github.com/RusZ/TextClassifier

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