Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications

Tutorial X

Classifying Documents with Respect to “Earnings” and Then Making a Predictive Model for the Target Variable Using Decision Trees, MARSplines, Naïve Bayes Classifier, and K-Nearest Neighbors with STATISTICA Text Miner

Contents

Introduction: Automatic Text Classification

Data File with File References

Specifying the Analysis

Processing the Data Analysis

Saving the Extracted Word Frequencies to the Input File

Initial Feature Selection

General Classification and Regression Trees

K-Nearest Neighbors Modeling

Conclusion

Reference

Introduction: Automatic Text Classification

This example is based on the “classic” Reuters collection of documents. Specifically, 5,000 documents were selected from the Reuters-21578 database, which is a collection ...