class_11_05 - Statistical Data Mining ORIE 474 Fall 2007...

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Statistical Data Mining ORIE 474 Fall 2007 Tatiyana Apanasovich 11/05/07 Artificial Neural Networks
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[Artificial] Neural Networks A class of powerful, general-purpose tools readily applied to: Prediction Classification Clustering Biological Neural Net (human brain) is the most powerful – we can generalize from experience What are (everyday) computer systems good at. .. and not so good at? Good at Not so good at Rule-based systems: doing what the programmer wants them to do Dealing with noisy data Dealing with unknown environment data Massive parallelism Fault tolerance Adapting to circumstances
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Neural Networks Computerized Neural Nets attempt to bridge the gap Predicting time-series in financial world Diagnosing medical conditions Identifying clusters of valuable customers Fraud detection Etc…
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Neural Networks When applied in well-defined domains, their ability to generalize and learn from data “mimics” a human’s ability to learn from experience. Very useful in Data Mining…better results are the hope Drawback – training a neural network results in internal weights distributed throughout the network making it difficult to understand why a solution is valid
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Real Estate Appraiser
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This note was uploaded on 12/23/2009 for the course ORIE 474 at Cornell University (Engineering School).

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class_11_05 - Statistical Data Mining ORIE 474 Fall 2007...

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