This index ranges from 0 to 1, zero where all observations belong to a class and 1 where every observation is random noise. For optimization or best decision of a leaf node we need limit of Gini ...
The goal of anomaly detection is to identify unusual or suspicious cases based on deviation from the norm within data that is seemingly homogeneous. Anomaly detection is an important tool: in data exploration and unsupervised learning The model trains on data that ishomogeneous, that is allcaseclassHaystacks and Needles: Anomaly Detection …
Although many researchers have tried to apply a various multiple-criteria decision analysis (MCDA) technique to select the most appropriate mining method, …
TY - JOUR. T1 - Data Mining with Decision Trees: Theory and Applications. AU - Holzinger, Andreas. PY - 2015. Y1 - 2015. M3 - Article. SN - 1468-4535
The main aim of this research is to develop a decision support system based on MCDM methods and use FUZZY logic to resolve uncertainties in the Underground …
In this paper, we present an aggregate production planning (APP) model applied to a Portuguese firm that produces construction materials. A multiple criteria mixed integer linear programming (MCMILP) model is developed with the following performance criteria: (1) maximize profit, (2) minimize late orders, and (3) minimize work force level …
Step 6: Execute the interactive decision process. The decision making process is terminated if the decision maker accepts the compromised production plan. Otherwise, the decision maker can decrease the span of fuzzy numbers sequentially by accumulating market information or modifying the model until a satisfactory production …
and visual impacts on surrounding lands; 2) maximize access to the aggregates; 3) maximize use of equipment and earth materials in shaping new lands; and 4) create stable, productive, and attractive lands through the mining process. Key Words: aggregate mining; site planning; land shaping. I Paper presented at the 1993 National Meeting
Kansei is a Japanese word, which refers to the human subjective feeling and impression [1].As shown in Fig. 1 [2], the Kansei features of a product manifest through its shape, material, color, and other factors, ultimately convey through a series of adjectives, such as "fashionable" or "classical".Consumer Kansei needs (CKN) denote preferences …
Modelling, estimation and simulation of new variables for new forms of mining—deep mining, particularly block caving, and solution mining. (4) Flexibility in …
Decision theory is concerned with the reasoning underlying an agent's choices, whether this is a mundane choice between taking the bus or getting a taxi, or a more far-reaching choice about whether to pursue a demanding political career. ... Under certain assumptions, the overall or aggregate preference ordering is compatible with EU …
This 2nd Edition is dedicated entirely to the field of decision trees in data mining; to cover all aspects of this important technique, as well as improved or new methods and techniques developed after the publication of the first edition. Decision trees have become one of the most powerful and popular approaches in knowledge discovery …
To develop strategic insights regarding the aggregate mining disputes in the province of Ontario, Canada, and to better understand their structured power hierarchies, we developed a two-level ...
This paper discussed a transparent, user-friendly technique which simplifies mining method selection even though it is driven by a powerful and proven decision-making process. …
Approaches to Aggregation and Decision Making—A Health Economics Approach: ... the problem is how best to aggregate the benefits enjoyed and the costs borne by individuals into a societal statement of value. Bator [1] proposes ... and the multi-attribute utility theory (MAUT). In the simplest form (linear MAUT), the value score is a …
decision theory to real-world problems to help companies ... (White, 1990). Whilst separately developed, both data mining and decision analysis have conceptual basic denominators, providing systematic methods for problem solving and decision making in view of objectives (decision ... aggregate the opinions of the group decision makers on
Data mining techniques and extracting patterns from large datasets play a vital role in knowledge discovery. Most of the decision makers encounter a large number of decision rules resulted from association rules mining. Moreover, the volume of datasets brings a new challenge to extract patterns such as the cost of computing and inefficiency …
Learn the principles and methods of forecasting from experts in the field. This article covers the theory and practice of forecasting in various domains and applications.
The ''helpfulness'' feature of online user reviews helps consumers cope with information overloads and facilitates decision-making. However, many online user reviews lack sufficient helpfulness votes for other users to evaluate their true helpfulness ...
Aggregates are critical resources for infrastructure and development, but mining operations can be disruptive to nearby communities. We examine a conflict …
Abstract Mineral aggregate as a stable, inexpensive, and available material has a fundamental role in engineering behaviors of concrete and its economy. When incompetent and conflicting decision-making criteria such as technical, economic, environmental, and so forth are realized in choosing borrow sources, the problem …
Mining Method Selection (MMS) is one of the important decisions in the mining design. The appropriate decision guarantees economic exploitation and an …
Each cell holds an aggregate data value, corresponding to the data point in multidimensional space. ... provide fast access to precomputed, summarized data, thereby benefiting on-line analytical processing as well as data mining. The lowest level of a data cube (base cuboid) ... Decision-tree induction method; To find Good Subset for Original ...
Understanding Decision Trees. A flexible and comprehensible machine learning approach for classification and regression applications is the decision tree.The conclusion, such as a class label for classification or a numerical value for regression, is represented by each leaf node in the tree-like structure that is constructed, with each …
Decision-making is a crucial skill that has a central role in everyday life and is necessary for adaptation to the environment and autonomy. It is the ability to choose between two or more options, and it has been studied through several theoretical approaches and by different disciplines. In this overview article, we contend a theoretical …
Data Mining with Decision Trees: Theory and Applications. Andreas Holzinger (Medical University Graz) Online Information Review. ISSN: 1468-4527. Article publication date: 8 June 2015. Downloads. 1336 Article view Figure view Cited (5) cite article Citation. Andreas Holzinger (2015), "Data Mining with Decision ...
Improving the MMS decision-making process for the coal mining companies. Provision of a systematic and unbiased approach that caters for subjective and objective analysis in MMS. Better insight and understanding of factors that affect coal MMS.
Currently, machine learning has limited applications in modeling wildfire evacuation decision-making; however, it has been widely applied in modeling people's travel mode choices in recent years ...
Social discrimination (e.g., against females) arising from data mining techniques is a growing concern worldwide. In recent years, several methods have been proposed for making classifiers learned over discriminatory data discrimination-aware. ... We relate both solutions with decision theory for better understanding of the process. …
Rock minerals such as dimension and crushed stones and sands and gravels (aggregates) are indispensable materials for the building and construction industries. The growth in demand for these resources causes intensification of mining operations (and their consequent environmental impacts) and transport problems in …
A decision tree is a non-parametric supervised learning algorithm, which is utilized for both classification and regression tasks. ... Entropy is a concept that stems from information theory, which measures the impurity of the sample values. It is defined with by the following formula, where: ... IBM SPSS Modeler supports the entire data mining ...
Grey Theory is a mathematical theory that was proposed in 1982 by Deng to solve problems with uncertainty and incomplete information. The grey theory consists of five parts; Grey prediction model, Grey relational analysis (GRA), Grey decision, Grey programming, and Grey control. The area of interest for decision makers is the GRA.
In addition to the utilitarian and egalitarian cases, we can use p ∈ [2.. ∞) for computing different consensus. To illustrate the semantics of the ethical principle p and its impact on the consensus, we show a test case (with fabricated data) in Fig. 1, which plots the judgements of 25 individuals on two objects.The circles represent the individuals' …
Working with a dedicated partner with industry expertise makes a difference, providing clarity and confidence in decision-making within this dynamic investment sector. ... For those in aggregate mining, there is an opportunity to give back by donating unused or exhausted land. By gifting land for recreational, conservation, or philanthropic ...
My thesis briefly discusses decision-making basic theory, in particular the deliberation method, and applies it to decision-making in the mining sector when making investment …
Decision rules for machining method chains mined from historical machining documents can help technologists quickly design new machining method chains. However, the main factor that limits the practical application of existing rough set models is that the boundary regions are too large. Therefore, a decomposition-reorganization method …
