Twenty-two decision tree, nine statistical, and two neural network algorithms are compared on thirty-two datasets in terms of classification accuracy, training time, and (in the ca...
Most classification algorithms receive as input a set of attributes of the classified objects. In many cases, however, the supplied set of attributes is not sufficient for creatin...
We describe an efficient technique to weigh word-based features in binary classification tasks and show that it significantly improves classification accuracy on a range of proble...
Justin Martineau, Tim Finin, Anupam Joshi, Shamit ...
Empirical search is a strategy used during the installation of library generators such as ATLAS, FFTW, and SPIRAL to identify the algorithm or the version of an algorithm that del...
Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and need no parameter tuning. We presen...