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00000cam a2200000Mu 4500 |
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EBOOKCENTRAL_on1347027483 |
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OCoLC |
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20240329122006.0 |
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m o d |
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cr cnu|||||||| |
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230209s2012 xx o ||| 0 eng d |
| 040 |
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|a EBLCP
|b eng
|c EBLCP
|d OCLCQ
|d OCLCO
|d OCLCQ
|d EBLCP
|d OCLCQ
|d OCLCL
|d OCLCQ
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| 020 |
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|a 9781118439234
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| 020 |
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|a 1118439236
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| 035 |
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|a (OCoLC)1347027483
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| 082 |
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4 |
|a 006.3/12
|q OCoLC
|2 23/eng/20230216
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| 049 |
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|a UAMI
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| 100 |
1 |
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|a Anderson, Russell K.
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| 245 |
1 |
0 |
|a Visual Data Mining
|h [electronic resource] :
|b The VisMiner Approach.
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| 260 |
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|a Newark :
|b John Wiley & Sons, Incorporated,
|c 2012.
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| 300 |
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|a 1 online resource (210 p.).
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| 490 |
1 |
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|a New York Academy of Sciences Ser.
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| 500 |
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|a Description based upon print version of record.
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| 505 |
0 |
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|a Visual Data Mining: THE VISMINER APPROACH -- Contents -- Preface -- Acknowledgments -- 1. Introduction -- Data Mining Objectives -- Introduction to VisMiner -- The Data Mining Process -- Initial Data Exploration -- Dataset Preparation -- Algorithm Selection and Application -- Model Evaluation -- Summary -- 2. Initial Data Exploration and Dataset Preparation Using VisMiner -- The Rationale for Visualizations -- Tutorial -- Using VisMiner -- Initializing VisMiner -- Initializing the Slave Computers -- Opening a Dataset -- Viewing Summary Statistics -- Exercise 2.1 -- The Correlation Matrix
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| 505 |
8 |
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|a Exercise 2.2 -- The Histogram -- The Scatter Plot -- Exercise 2.3 -- The Parallel Coordinate Plot -- Exercise 2.4 -- Extracting Sub-populations Using the Parallel Coordinate Plot -- Exercise 2.5 -- The Table Viewer -- The Boundary Data Viewer -- Exercise 2.6 -- The Boundary Data Viewer with Temporal Data -- Exercise 2.7 -- Summary -- 3. Advanced Topics in Initial Exploration and Dataset Preparation Using VisMiner -- Missing Values -- Missing Values -- An Example -- Exploration Using the Location Plot -- Exercise 3.1 -- Dataset Preparation -- Creating Computed Columns -- Exercise 3.2
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| 505 |
8 |
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|a Aggregating Data for Observation Reduction -- Exercise 3.3 -- Combining Datasets -- Exercise 3.4 -- Outliers and Data Validation -- Range Checks -- Fixed Range Outliers -- Distribution Based Outliers -- Computed Checks -- Exercise 3.5 -- Feasibility and Consistency Checks -- Data Correction Outside of VisMiner -- Distribution Consistency -- Pattern Checks -- A Pattern Check of Experimental Data -- Exercise 3.6 -- Summary -- 4. Prediction Algorithms for Data Mining -- Decision Trees -- Stopping the Splitting Process -- A Decision Tree Example -- Using Decision Trees -- Decision Tree Advantages
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| 505 |
8 |
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|a Limitations -- Artificial Neural Networks -- Overfitting the Model -- Moving Beyond Local Optima -- ANN Advantages and Limitations -- Support Vector Machines -- Data Transformations -- Moving Beyond Two-dimensional Predictors -- SVM Advantages and Limitations -- Summary -- 5. Classification Models in VisMiner -- Dataset Preparation -- Tutorial -- Building and Evaluating Classification Models -- Model Evaluation -- Exercise 5.1 -- Prediction Likelihoods -- Classification Model Performance -- Interpreting the ROC Curve -- Classification Ensembles -- Model Application -- Summary -- Exercise 5.2
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| 505 |
8 |
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|a Exercise 5.3 -- 6. Regression Analysis -- The Regression Model -- Correlation and Causation -- Algorithms for Regression Analysis -- Assessing Regression Model Performance -- Model Validity -- Looking Beyond R2 -- Polynomial Regression -- Artificial Neural Networks for Regression Analysis -- Dataset Preparation -- Tutorial -- A Regression Model for Home Appraisal -- Modeling with the Right Set of Observations -- Exercise 6.1 -- ANN Modeling -- The Advantage of ANN Regression -- Top-Down Attribute Selection -- Issues in Model Interpretation -- Model Validation -- Model Application -- Summary
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| 500 |
|
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|a 7. Cluster Analysis
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| 590 |
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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| 655 |
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0 |
|a Electronic books.
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| 758 |
|
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|i has work:
|a Visual data mining (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCH3pwRR3Ky4hK3fWKWVq6X
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
| 776 |
0 |
8 |
|i Print version:
|a Anderson, Russell K.
|t Visual Data Mining
|d Newark : John Wiley & Sons, Incorporated,c2012
|z 9781119967545
|
| 830 |
|
0 |
|a New York Academy of Sciences Ser.
|
| 856 |
4 |
0 |
|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=7103658
|z Texto completo
|
| 938 |
|
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|a ProQuest Ebook Central
|b EBLB
|n EBL7103658
|
| 994 |
|
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|a 92
|b IZTAP
|
