MECH 534 Computer-Based Modeling and Simulation Notes on Decision Trees and Monte Carlo Simulations Prepared by Prof. Cagatay Basdogan Decision Trees: Decision trees
ثبت نشده
چکیده
Decision Trees: Decision trees are typically used to support decision-making in an uncertain environment. For example, in making engineering decisions for product manufacturing, the engineer usually faces multiple unknowns that make it difficult to choose a winning option. Although the engineer does not know what the overall outcome will be, he generally has some knowledge—or at least an opinion—about what the possible outcomes for the various phases of the operation and how likely each is to occur. This information can be compiled to help the option that is most likely to yield favorable results. Decision trees make this type of analysis relatively easy to apply.
منابع مشابه
Tagging heavy flavours with boosted decision trees
This paper evaluates the performance of boosted decision trees for tagging b-jets. It is shown, using a Monte Carlo simulation of WH → lνqq̄ events that boosted decision trees outperform feed-forward neural networks. The results show that for a b-tagging efficiency of 90% the b-jet purity given by boosted decision trees is almost 20% higher than that given by neural networks.
متن کاملAlternative Approaches for Solving Real-Options Problems
B et al. (2005) describe an approach for using traditional decision analysis tools to solve real-option valuation problems. Their approach calls for a mix of discounted cash flow analysis and risk-neutral valuation methods and is implemented using Monte Carlo simulation and binomial decision trees. In this note, I critique their approach and discuss some alternative approaches for solving these...
متن کاملPredicting The Type of Malaria Using Classification and Regression Decision Trees
Predicting The Type of Malaria Using Classification and Regression Decision Trees Maryam Ashoori1 *, Fatemeh Hamzavi2 1School of Technical and Engineering, Higher Educational Complex of Saravan, Saravan, Iran 2School of Agriculture, Higher Educational Complex of Saravan, Saravan, Iran Abstract Background: Malaria is an infectious disease infecting 200 - 300 million people annually. Environme...
متن کاملProbabilistic Multi Objective Optimal Reactive Power Dispatch Considering Load Uncertainties Using Monte Carlo Simulations
Optimal Reactive Power Dispatch (ORPD) is a multi-variable problem with nonlinear constraints and continuous/discrete decision variables. Due to the stochastic behavior of loads, the ORPD requires a probabilistic mathematical model. In this paper, Monte Carlo Simulation (MCS) is used for modeling of load uncertainties in the ORPD problem. The problem is formulated as a nonlinear constrained mul...
متن کاملA multivariate approach to heavy flavour tagging with cascade training
This paper compares the performance of artificial neural networks and boosted decision trees, with and without cascade training, for tagging b-jets in a collider experiment. It is shown, using a Monte Carlo simulation of WH → lνqq̄ events, that boosted decision trees outperform artificial neural networks. Furthermore, cascade training can substantially improve the performance of both boosted dec...
متن کامل