Supervised machine learning: A review of classification techniques

SB Kotsiantis, I Zaharakis, P Pintelas - … intelligence applications in …, 2007‏ - books.google.com
The goal of supervised learning is to build a concise model of the distribution of class labels
in terms of predictor features. The resulting classifier is then used to assign class labels to …

Interestingness measures for data mining: A survey

L Geng, HJ Hamilton - ACM Computing Surveys (CSUR), 2006‏ - dl.acm.org
Interestingness measures play an important role in data mining, regardless of the kind of
patterns being mined. These measures are intended for selecting and ranking patterns …

[ספר][B] Machine learning: the art and science of algorithms that make sense of data

P Flach - 2012‏ - books.google.com
As one of the most comprehensive machine learning texts around, this book does justice to
the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's …

[ספר][B] Evaluating learning algorithms: a classification perspective

N Japkowicz, M Shah - 2011‏ - books.google.com
The field of machine learning has matured to the point where many sophisticated learning
approaches can be applied to practical applications. Thus it is of critical importance that …

Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation

DMW Powers - arxiv preprint arxiv:2010.16061, 2020‏ - arxiv.org
Commonly used evaluation measures including Recall, Precision, F-Measure and Rand
Accuracy are biased and should not be used without clear understanding of the biases, and …

Data mining: practical machine learning tools and techniques with Java implementations

IH Witten, E Frank - Acm Sigmod Record, 2002‏ - dl.acm.org
Witten and Frank's textbook was one of two books that 1 used for a data mining class in the
Fall of 2001. The book covers all major methods of data mining that produce a knowledge …

[ספר][B] Foundations of rule learning

J Fürnkranz, D Gamberger, N Lavrač - 2012‏ - books.google.com
Rules–the clearest, most explored and best understood form of knowledge representation–
are particularly important for data mining, as they offer the best tradeoff between human and …

[PDF][PDF] Practical machine learning tools and techniques

IH Witten, E Frank, MA Hall, CJ Pal, M Data - Data mining, 2005‏ - alvarestech.com
The convergence of computing and communication has produced a society that feeds on
information. Yet most of the information is in its raw form: data. If data is characterized as …

Performance evaluation in machine learning: the good, the bad, the ugly, and the way forward

P Flach - Proceedings of the AAAI conference on artificial …, 2019‏ - aaai.org
This paper gives an overview of some ways in which our understanding of performance
evaluation measures for machine-learned classifiers has improved over the last twenty …

Knowledge discovery from data streams

J Gama, PP Rodrigues, E Spinosa… - Web Intelligence and …, 2010‏ - ebooks.iospress.nl
In the last two decades, machine learning research and practice has focused on batch
learning, usually with small datasets. Nowadays there are applications in which the data are …