Searching for Decision Tree Support Confidence information? Find all needed info by using official links provided below.
https://support.bigml.com/hc/en-us/articles/206616219-How-is-the-confidence-and-expected-error-being-estimated-in-a-decision-tree-model-
The selected prediction path assumes that at least 60 instances (customers), which represent 2.25% of the data, will churn at the end of the month with a confidence of 93.98%. For the regression trees (with a numeric objective field) BigML has expected error, which follows the same approach as the confidence for classification models. It means ...
https://docs.oracle.com/cd/B28359_01/datamine.111/b28129/algo_decisiontree.htm
About Decision Tree. The Decision Tree algorithm, like Naive Bayes, is based on conditional probabilities. Unlike Naive Bayes, decision trees generate rules.A rule is a conditional statement that can easily be understood by humans and easily used within a database to identify a set of records.
https://datascience.stackexchange.com/questions/41972/how-to-reduce-the-number-of-rules-in-decision-tree-with-support-and-confidence
The following is a set of rules in decison tree. How to reduce the number of rules in the set with Support and Confidence? If Ascites = 'Yes' then if Class = 'Live' then if Spiders = 'Yes' then if Bilirubin <= 2.2 then if Sex = 'Female' then Histology ='No’. Its dataset is as follows.
https://www.decision-making-confidence.com/decision-tree-software.html
In the computing world, the decision tree is a very popular algorithm for data mining and machine learning. In medicine, clinical decision support systems are used for such things as triage, diagnosis, and analysis of patient data.
http://www.ise.bgu.ac.il/faculty/liorr/confdtree.pdf
decision trees to better classify outlier instances. This method, which can be applied on any decision trees algorithm, uses confidence intervals in order to identify these hard-to-classify instances and proposes alternative routes. The experimental study indicates that the proposed post-processing method
https://docs.rapidminer.com/latest/studio/operators/modeling/predictive/trees/parallel_decision_tree.html
Decision Tree; Decision Tree (Concurrency) Synopsis This Operator generates a decision tree model, which can be used for classification and regression. Description. A decision tree is a tree like collection of nodes intended to create a decision on values affiliation to a class or an estimate of a numerical target value.
http://www2.cs.uh.edu/~ordonez/pdfwww/w-2006-HIKM-ardtmed.pdf
Comparing Association Rules and Decision Trees for Disease Prediction Carlos Ordonez University of Houston Houston, TX, USA ABSTRACT Association rules represent a promising technique to nd hidden patterns in a medical data set. The main issue about mining association rules in …Cited by: 135
https://www.academia.edu/648890/Support_vs_Confidence_in_Association_Rule_Algorithms
The discovery of interesting association relationships among large amounts of business transactions is currently vital for making appropriate business decisions. There are currently a variety of algorithms to discover association rules. Some of these
https://en.wikipedia.org/wiki/Association_rule_learning
Association rule learning is a rule-based machine learning method for discovering interesting relations between variables in large databases. It is intended to identify strong rules discovered in databases using some measures of interestingness.
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