Skip to search formSkip to main contentSkip to account menu

CN2 algorithm

The CN2 induction algorithm is a learning algorithm for rule induction. It is designed to work even when the training data is imperfect. It is based… 
Wikipedia (opens in a new tab)

Related topics

Related topics

3 relations
Algorithmic learning theoryID3 algorithmRule induction

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
Handling Missing Values for the CN2 Algorithm
Missing values are existed in several practical data sets. Machine Learning algorithms, such as CN2, require missing values in a… 
2017
2017
Bias stress in PDI-CN2 and P3HT studied with Kelvin Probe Force Microscopy
2016
2016
Pruning methods for rule induction
Machine learning is a research area within computer science that is mainly concerned with discovering regularities in data. Rule… 
2014
2014
First principles investigations of electronic, photoluminescence and charge transfer properties of the Naphtho[2,1-b:6,5-b ']difuran and its derivatives for OFET
We have designed new derivatives of naphtha [2,1-b:6,5-b′] difuran as DPNDF-CN1 and DPNDF-CN2. The molecular structures of DPNDF… 
2013
2013
Using Strongly Typed Genetic Programming for knowledge discovery of course quality from e-learning's web log
Learning Management System (LMS) has become the popular instrument in academic institutions by providing feasible pedagogical… 
2013
2013
Modeling of algorithms of inductive concept formation in “noisy” databases
The problem is inductive concept formation in the case of the processing of incomplete, inaccurate, and inconsistent information… 
2009
2009
Argumentation-based Distributed Induction
Argumentation can be used by a group of agents to discuss about the validity of hypotheses. In this paper we propose an… 
2005
2005
Rule Induction for Click-Stream Analysis: Set Covering and Compositional Approach
We present a set covering algorithm and a compositional algorithm to describe sequences of www pages visits in click-stream data… 
Review
2004
Review
2004
Meta-Learner for Unknown Attribute Values Processing: Dealing with Inconsistency of Meta-Databases
Efficient robust data mining algorithms should comprise some routines for processing unknown (missing) attribute values when… 
2000
2000
A report on experiments with weighted relative accuracy in CN2
In this report, the prediction performances of two rule evaluation measures, accuracy and weighted relative accuracy, are… 
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy (opens in a new tab), Terms of Service (opens in a new tab), and Dataset License (opens in a new tab)