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Decision tree learning - Wikipedia

It is one of the predictive modelling approaches used in statistics, data mining and machine learning. Tree models where the target variable can take a discrete set of values are called classification trees; ...

Application of Tunnel Boring Machines in Underground Mine Development

space and weight limitations imposed by the mine’s shaft. Some of the features of the machine are given in Table 1. Figure 2. San Manual TBM (Robbins). ...

Crime Pattern Detection Using Data Mining

attributes here to deal with limitations of various out of the box clustering tools and techniques. This easy to implement data mining framework works with the geo-spatial plot of crime and helps to improve the productivity of the detectives and other law ...

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The Exception for Text and Data Mining (TDM) in the Proposed Directive on Copyright in the Digital Single Market – Legal Aspects

Do existing exceptions and limitations apply to TDM? 8 Which problems researchers face in applying existing exceptions to TDM? 12 Would an “opening clause” serve public interest? 15 4. ...

Cluster Analysis vs. Market Segmentation - Data Mining Consulting Services by BIsolutions

Data mining consulting services- Improve your business performance by turning data into smart decisions. ... Limitations and Problems of Traditional Cluster Analysis Methods Need to specify K (number of clusters) in advance Applicable only for interval Sizes ...

Problems in the mining industry in South africa - ECDPM

The current turbulence in the mining industry in South Africa has its roots in several different factors. First, the fall in global demand for platinum and other minerals due to recession; second, the consequences of the Marikana disaster in destabilising labour relations ...

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Data mining tools: Advantages and disadvantages of implementation

I will take your question to mean the application of data mining technologies, such as SAS, SPSS or Microsoft Data Mining to solve specific business problems. Business problems need to be solved, and often technology is required. Many problems that can be solved with data mining technologies can

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Crime Pattern Detection Using Data Mining

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Problems and Limitations of Circular Knitted Structures - Textile Learner

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Hope and limitations of machine learning in market risk assessment

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The real-world potential and limitations of artificial intelligence | McKinsey & Company

of the things that’s a little bit new about the current generations of AI is what we call machine learning—in the sense that ... are remarkable in the sense that we can take things we’ve learned over here and apply them to totally different problems that we ...

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Machine Vision: Approaches and Limitations | IntechOpen

Machine Vision: Approaches and Limitations By Moises Rivas Lopez, Oleg Sergiyenko and Vera Tyrsa Published: November 1st 2008 DOI: 10.5772/6156 Home > Books > Computer Vision Downloaded: 5711 Download chapter PDF Citations in RIS format Share ...

Discrete Optimization Problems in Data Analysis, Clustering, Pattern Recognition, Machine Learning, Data Mining and Big Data Processing ...

Discrete Optimization Problems in Data Analysis, Clustering, Pattern Recognition, Machine Learning, Data Mining and Big Data Processing | (1) Analysis and disclosure of the computational complexity of problems, (2) Efficient algorithms with performance ...

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Machine Vision: Approaches and Limitations | IntechOpen

Machine Vision: Approaches and Limitations By Moises Rivas Lopez, Oleg Sergiyenko and Vera Tyrsa Published: November 1st 2008 DOI: 10.5772/6156 Home > Books > Computer Vision Downloaded: 5711 Download chapter PDF Citations in RIS format Share ...

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Surface Mining Methods and Equipment - Encyclopedia of Life Support Systems

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Groundwater Flow Modelling Applications in Mining: Scopes and Limitations

270 CHAPTER 05 Figure 2 Example of an acceptable time of work by modelling activity. LIMITATIONS Even though the previously shown methodology is widely known to modellers, in most of the mining projects data is limited. In general, the availability of data for ...

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