[PDF] Top 20 Machine Learning Methods for Uncertainty Estimation and Decision-making.
Has 10000 "Machine Learning Methods for Uncertainty Estimation and Decision-making." found on our website. Below are the top 20 most common "Machine Learning Methods for Uncertainty Estimation and Decision-making.".
Machine Learning Methods for Uncertainty Estimation and Decision-making.
... CDF estimation as the objective function used to train the neural ...distribution estimation with neural network [ Wang (1994), Likas (2001), Magdon-Ismail and Atiya (2002), Zegers and Johnson (2006) and ... See full document
101
Multi Criteria Decision Making Technique For Machine Learning Algorithms: Iterative And Non-Iterative Algorithms
... solved. Machine learning is a method that enables the computer system to have the intelligence by analyzing the data and building an automated analytical ...in machine learning are broadly ... See full document
12
A Reactive Search Optimization approach to interactive decision making
... of learning in changing conditions is known in the machine learning community as learning under concept drift ...the decision maker to change her preferences during the interactive ... See full document
95
Decision making in machine tool selection: An integrated approach with SWARA and COPRAS-G methods
... Though DMs’ judgments, education and expertise play important roles in the success or failure of manufacturing decisions, sometimes their evaluations or judgments are vague and imprecise. These inaccuracies can cause ... See full document
13
Flexible Statistical Machine Learning Methods for Optimal Treatment Decision.
... treatment regime can individualize treatment and get optimal output for each patient. Different treatments include differences in treatment type and dosage level variation. For some diseases, treatment adjustment is ... See full document
91
A Review On Big Data With Machine Learning And Fuzzy Logic For Better Decision Making
... Fuzzy logic is a "degrees of truth" approach rather than the "true or false" (1 or 0). The idea of fuzzy logic was first introduced by Dr. LotfiZadeh from University of California in the 1960s.Fuzzy logic ... See full document
5
Survey on Artificial Intelligence in Healthcare
... or Machine learning in current times serves as the primary choice for data mining and big data ...analytic methods has made possible the recent successful applications of AI in healthcare AI ... See full document
5
Decision Tree Algorithms for Diagnosis of Cardiac Disease Treatment
... database. Decision tree learning algorithm has been successfully used in expert systems in finding the ...and methods for building decision tree, such as ID3, ...for decision ... See full document
7
Improving the Prediction of Survival in Cancer Patients by Using Machine Learning Techniques: Experience of Gene Expression Data: A Narrative Review
... survival estimation (37, ...clinical decision- making, provide individualized treatment, man- age the patients, and reduce the cost puts patients under pressure and the healthcare ...number, ... See full document
8
A transfer learning aided decision support system for multi cloud brokers
... ments: Decision Support, Actuator, and Knowledge Base. The Decision Support module, equipped with machine learning models, is at the heart of Daleel’s ...Analysis, Learning, and ... See full document
214
Comparative Analysis on Algorithm that can be used for Stock Market Prediction
... traditional methods such as outlier detection [4] there are various machine learning algorithms that are discussed in this paper, section I explains how decision tree and random forest ... See full document
5
Scientific uncertainty and decision making
... In the same way, despite acts, outcomes and states all being the same sort of things, they are dealt with differently. Indeed, one might think of Savage’s ap- proach as formalising the separation that is implicit in the ... See full document
278
Machine Learning for Clinical Decision-Making: Challenges and Opportunities
... deep learning (DL)) has emerged as a convenient approach to boost data quality, standardization, and reduce variability in ...for learning purposes (Kazeminia et ...enhancement methods using DL have ... See full document
38
Designing a Machine Learning Decision Tree for Information Systems: A study into the implementation of supervised and unsupervised machine learning methods
... supervised machine learning. This type of machine learning needs labelled data in order to accurately label a new feature set, by either classifying new feature sets (classification) or ... See full document
42
Decision making under risk with continuous states of nature
... real-world decision making situation in economics, politics, environmental protection, ...with uncertainty regarding future state of the ...as decision making under ...as ... See full document
6
The evaluationof decision making process and implementation of local content subject learning materialsat the islamic senior high school (madrasah aliyah) in mataram west nusa tenggara Indonesia
... the learning instruments, it was also found that the only learning materials used by the teacher were only ...other learning materials were ready-used materials, which were not designed by the ...the ... See full document
5
Model for Object Detection using Computer Vision and Machine Learning for Decision Making
... In paper [14], they have discussed none contact hand motion classification technique for application to human-machine interfaces. This paper presents an effective none contact technique for the measurement of ... See full document
5
Machine Learning Methods of Effort Estimation and It’s Performance Evaluation Criteria
... different methods for estimation but there is no estimation method, which can present the best estimates in all various situations, and each technique can be suitable in the special ... See full document
7
Decision Making under Uncertainty in Tool Condition Monitoring
... possible methods of determining tool ...direct methods tend to be accurate, they are more complex and often not applicable to real machining ...Indirect methods involve the measurement of some ... See full document
12
Analysis of various Machine Learning Techniques to Detect Phishing Email
... email belongs to the “spam” or “good” email category. Separate datasets were generated to train and test the models. First, the data was split into training and test data. Then, the models were trained and evaluated. By ... See full document
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