2012,Data Mining (Third Edition) Chapter Knowledge Representation 4.1.2Attribute properties and dependencies Attributes have various properties important for their usage in machine learning anddata mining: Noisy
Mining Binary AttributesThe home of the Transactions of the Wessex Institute collection, providing on-line access to papers presented at the Institute's prestigious international conferences and from its State-of-the-Art in Science & Engineering publications.Costa, Joaquim P...
We consider the class of linear predictors over all logical conjunctions of binary attributes, which we refer to as the class of combinatorial binary models (CBMs) in this paper. CBMs are of high knowledge interpretability but naïve learning of them from labeled data requires exponentially high ...
This MATLAB function returns a fitted binary classification decision tree based on the input variables (also known as predictors, features, or attributes) contained in the table Tbl and output (response or labels) contained in Tbl.ResponseVarName.
The essential attributes of feature descriptors are that they should be invariant to geometric and photometric transformations and also be robust to clutter and occlusion. Feature descriptors are categorized into real-valued descriptors like SIFT, SURF, GLOH (gradient location and orientation histogram),...
In this paper, we are interested in determining relevant attributes for multi-class discrimination of binary data. Given a set of observations described by the presence or absence of a set of attributes and divided into groups, we seek to determine a sub
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Binary attributes in decision trees allow for using attribute quality measures that otherwise over-estimate multi-valued attributes, such as information gain and Gini-index. Binary decision trees are usually smaller than the ordinary ones, thus providing better generalization and better performance (e.g...
In subject area: Computer Science Binary Classification is defined as the process of assigning an individual to one of two categories based on a series of attributes. It involves making decisions between two elements, such as 'diagnosis of disease' and 'diagnosis of no disease', by analyzing d...