Combining Multiple Diagnostic Trouble Codes into a Single Decision Tree
نویسندگان
چکیده
منابع مشابه
CMDTL1 : Combining Multiple Classifiers into a Cost-Sensitive Decision Tree
For many real-life applications, such as medical diagnosis, cost of a decision is an important practical criterion which can not be ignored. The state-of-the-art C4.5 algorithm for inductive learning was not developed with this criterion in mind. However, some well-developed approaches exist that induce decision tree, giving importance to the cost criterion. This paper presents a general framew...
متن کاملCombining Multiple Host-Based Detectors Using Decision Tree
As the information technology grows interests in the intrusion detection system (IDS), which detects unauthorized usage, misuse by a local user and modification of important data, have been raised. In the field of anomaly-based IDS several artificial intelligence techniques are used to model normal behavior. However, there is no perfect detection method so that most of IDSs can detect the limit...
متن کاملDiagnostic decision tree in dementia
Diagnostic decision tree in dementia Diagnostic criteria for dementia include memory impairment plus impairment in at least one other cog-nitive function, including aphasia, apraxia, agnosia, or disturbance in executive functioning. 4 These deficits must represent a decline from a previous level of functioning and be sufficiently severe to cause significant impairment in social or occupational ...
متن کاملSingle versus Multiple Tree Genetic Programming for Dynamic Decision Making
This paper considers genetic programming (GP) for dynamic decision making. Standard genetic programming only uses a single decision tree for decision making. In contrast, this paper proposes a general multiple tree framework for dynamic decision problems, where evaluation is contingent on the previous output of the program. The working hypothesis is that “recurrent” multiple trees are superior ...
متن کاملDecision Forest: Combining the Predictions of Multiple Independent Decision Tree Models
The techniques of combining the results of multiple classification models to produce a single prediction have been investigated for many years. In earlier applications, the multiple models to be combined were developed by altering the training set. The use of these so-called resampling techniques, however, poses the risk of reducing predictivity of the individual models to be combined and/or ov...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IFAC-PapersOnLine
سال: 2016
ISSN: 2405-8963
DOI: 10.1016/j.ifacol.2016.08.081