Results 271 to 280 of about 3,746,451 (299)
Some of the next articles are maybe not open access.
On decision trees for orthants
Information Processing Letters, 1997zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources
On Optimization of Decision Trees
2005In the paper algorithms are considered which allow to consecutively optimize decision trees for decision tables with many-valued decisions relatively different complexity measures such as number of nodes, weighted depth, average weighted depth, etc. For decision tables over an arbitrary infinite restricted information system [5] these algorithms have ...
Igor Chikalov +2 more
openaire +1 more source
Decision trees with AND, OR queries
Proceedings of Structure in Complexity Theory. Tenth Annual IEEE Conference, 2002We investigate decision trees in which one is allowed to query threshold functions of subsets of variables. We are mainly interested in the case where only queries of AND and OR are allowed. This model is a generalization of the classical decision tree model.
Yosi Ben-Asher, Ilan Newman
openaire +1 more source
On the Decision Trees with Symmetries
2018We introduce a propositional proof system based on decision trees utilizing symmetries of formulas. We refer to this proof system as decision trees with symmetries (\(\mathrm {SDT}\)). \(\mathrm {SDT}\) can be polynomially simulated by the proof system \(\mathrm {SR}\text {-}\mathrm {I}\) introduced by Krishnamurthy [7]; \(\mathrm {SR}\text {-}\mathrm {
openaire +2 more sources
Expert Systems with Applications, 2013
Univariate decision trees are classifiers currently used in many data mining applications. This classifier discovers partitions in the input space via hyperplanes that are orthogonal to the axes of attributes, producing a model that can be understood by human experts.
Asdrúbal López-Chau +3 more
openaire +1 more source
Univariate decision trees are classifiers currently used in many data mining applications. This classifier discovers partitions in the input space via hyperplanes that are orthogonal to the axes of attributes, producing a model that can be understood by human experts.
Asdrúbal López-Chau +3 more
openaire +1 more source
2002
Searching for binary partition of attribute domains is an important task in Data Mining, particularly in decision tree methods. The most important advantage of decision tree methods are based on compactness and clearness of presented knowledge and high accuracy of classification.
openaire +2 more sources
Searching for binary partition of attribute domains is an important task in Data Mining, particularly in decision tree methods. The most important advantage of decision tree methods are based on compactness and clearness of presented knowledge and high accuracy of classification.
openaire +2 more sources
Collegian, 2000
Financial cutbacks and budgetary constraints continue to be a part of government policy, and impact deeply on many aspects of daily life in Australia in the late 90s. Health care is not immune from these measures, and nurses and other allied health professionals are having to manage increasingly complex patient care with less funding and resources ...
openaire +2 more sources
Financial cutbacks and budgetary constraints continue to be a part of government policy, and impact deeply on many aspects of daily life in Australia in the late 90s. Health care is not immune from these measures, and nurses and other allied health professionals are having to manage increasingly complex patient care with less funding and resources ...
openaire +2 more sources
Explainable decision forest: Transforming a decision forest into an interpretable tree
Information Fusion, 2020Lior Rokach, Ömer Sagi
exaly
Decision aids for localized prostate cancer treatment choice: Systematic review and meta-analysis
Ca-A Cancer Journal for Clinicians, 2015Arnav Agarwal, Henrikki Santti
exaly
What is lacking in current decision aids on cancer screening?†
Ca-A Cancer Journal for Clinicians, 2013Sarah T Hawley, Donald E Nease
exaly