• Publications
  • Influence
The WEKA data mining software: an update
TLDR
This paper provides an introduction to the WEKA workbench, reviews the history of the project, and, in light of the recent 3.6 stable release, briefly discusses what has been added since the last stable version (Weka 3.4) released in 2003.
Data mining: practical machine learning tools and techniques, 3rd Edition
TLDR
This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining.
Data mining: practical machine learning tools and techniques with Java implementations
TLDR
This presentation discusses the design and implementation of machine learning algorithms in Java, as well as some of the techniques used to develop and implement these algorithms.
Classifier chains for multi-label classification
TLDR
This paper presents a novel classifier chains method that can model label correlations while maintaining acceptable computational complexity, and illustrates the competitiveness of the chaining method against related and state-of-the-art methods, both in terms of predictive performance and time complexity.
Data mining - practical machine learning tools and techniques, Second Edition
  • I. Witten, Eibe Frank
  • Computer Science
    The Morgan Kaufmann series in data management…
  • 22 June 2005
TLDR
This book describes a body of practical techniques that can extract useful information from raw data and shows how they work.
Generating Accurate Rule Sets Without Global Optimization
TLDR
This paper presents an algorithm for inferring rules by repeatedly generating partial decision trees, thus combining the two major paradigms for rule generation—creating rules from decision trees and the separate-and-conquer rule-learning technique.
KEA: practical automatic keyphrase extraction
TLDR
This paper uses a large test corpus to evaluate Kea’s effectiveness in terms of how many author-assigned keyphrases are correctly identified, and describes the system, which is simple, robust, and publicly available.
Data Mining: Practical Machine Learning Tools and Techniques, 3/E
TLDR
This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining.
Weka: Practical machine learning tools and techniques with Java implementations
The Waikato Environment for Knowledge Analysis (Weka) is a comprehensive suite of Java class libraries that implement many state-of-the-art machine learning and data mining algorithms. Weka is freely
Domain-Specific Keyphrase Extraction
TLDR
This paper shows that a simple procedure for keyphrase extraction based on the naive Bayes learning scheme performs comparably to the state of the art, and explains how this procedure's performance can be boosted by automatically tailoring the extraction process to the particular document collection at hand.
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