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# Part 7: Model Appraisal.

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7. Part 7: Model Evaluation. 7. Section 7: Model Evaluation. Appraisal Sorts. The Model Correlation instrument gives. C. KS. Outline insights Factual representation. ASE. 7. Section 7: Model Appraisal. Synopsis Measurements Outline. Expectation Sort. Measurement.
Transcripts
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7 Chapter 7: Model Assessment

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7 Chapter 7: Model Assessment

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Assessment Types The Model Comparison instrument gives C KS Summary insights Statistical design ASE

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7 Chapter 7: Model Assessment

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Summary Statistics Summary Prediction Type Statistic Accuracy/Misclassification Profit/Loss KS-measurement Decisions ROC Index (concordance) Gini coefficient 1,2,3,â¦ Rankings Average squared slip SBC/Likelihood p â E( Y ) ^ Estimates

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Summary Statistics Summary Prediction Type Statistic Accuracy/Misclassification Profit/Loss KS-measurement Decisions ROC Index (concordance) Gini coefficient 1,2,3,â¦ Rankings Average squared mistake SBC/Likelihood p â E( Y ) ^ Estimates

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Summary Statistics Summary Prediction Type Statistic Accuracy/Misclassification Profit/Loss KS-measurement Decisions ROC Index (concordance) Gini coefficient 1,2,3,â¦ Rankings Average squared lapse SBC/Likelihood p â E( Y ) ^ Estimates

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Comparing Models with Summary Statistics This show delineates the Model\'s utilization Comparison device, which gathers evaluation data from appended displaying hubs and empowers you to effortlessly think about model execution measures.

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7 Chapter 7: Model Assessment

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Decisions Sensitivity outlines Response rate diagrams Statistical Graphics Summary Prediction Type Statistic 1,2,3,â¦ Rankings p â E( Y ) ^ Estimates ...

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Apply model to acceptance information. Factual Graphics â Prediction Ranks approval information ...

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main 40% Prediction Ranks Select top n % cases. ...

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Sensitivity-Based Plots Count portion of essential result cases in determination. main 40% 1.0 affectability 0.0 ...

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False Positive Fraction Count division of optional result cases in determination. main 40% 1.0 affectability 0.0 1.0 false positive portion (1-specificity) ...

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ROC Chart Repeat for all choice divisions. 1.0 affectability 0.0 1.0 false positive portion (1-specificity) ...

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1.0 affectability 0.0 1.0 false positive division (1-specificity) ROC Index ROC Index (c-measurement) ...

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1.0 0.5 0% 100% 40% percent chose (decile) Response Rate Charts main 40% Select top n % cases. ...

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Cumulative Gain main 40% Count division of cases in choice with essential result. 1.0 aggregate increase 0.5 0% 100% 40% percent chose (decile) ...

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Cumulative Gains Chart Repeat for all determination parts. 1.0 combined increase 0.5 0% 100% percent chose (decile) ...

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Comparing Models with Statistical Graphics This show represents the utilization of measurable illustrations to think about models.

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Adjusting for Separate Sampling This exhibition outlines how to conform for partitioned examining in SAS Enterprise Miner.

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7 Chapter 7: Model Assessment

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Outcome Overrepresentation The specimen size is resolved not by the aggregate number of cases but rather by the quantity of cases in minimum basic result (generally essential). ...

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Separate Sampling Cases are examined independently from every result. Case: â¢ test every single essential cas â¢ coordinate every essential case by one or more auxiliary cases ...

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Separate Sampling Benefit â¢ Similar prescient force with littler case check

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Separate Sampling Consequences â¢ Must conform evaluation measurements and design â¢ Must change expectation gauges for inclination

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Adjusting for Separate Sampling (proceeded with) This exhibit delineates how to alter for discrete inspecting in SAS Enterprise Miner.

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Creating a Profit Matrix This show outlines how to make a benefit lattice.

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7 Chapter 7: Model Assessment

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Profit Matrices request disregard 14.86 0 essential result - 0.68 0 auxiliary result 0 benefit conveyance for request choice

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Profit Matrices request overlook 14.86 0 essential result - 0.68 0 optional result 0 benefit dispersion for request choice

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pick the bigger ^ Expected Profit Solicit = 14.86 p 1 â 0.68 p 0 Expected Profit Ignore = 0 Decision Expected Profits request disregard 14.86 0 essential result - 0.68 0 optional result 0 ...

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Decision Threshold request overlook 14.86 0 essential result - 0.68 0 auxiliary result 0 choice limit ^ p 1 â¥ 0.68/15.54 ï Solicit ^ p 1 < 0.68/15.54 ï Ignore

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Average Profit request disregard 14.86 0 essential result - 0.68 0 optional result 0 normal benefit Average benefit = (14.86ï\' N PS â 0.68 ï\' N SS )/N PS = # requested essential result cases N SS = # requested optional result cases N = aggregate number of appraisal cases

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Evaluating Model Profit This exhibition outlines seeing the outcomes of joining a benefit grid.

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Viewing Additional Assessments This show represents a few different evaluations of conceivable hobby.

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Optimizing with Profit (Optional) This show represents improving your model entirely on benefit.

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Exercise 1 This activity strengthens the ideas examined already.

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7 Chapter 7: Model Assessment

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Assessment Tools Review Compare model outline insights and measurable representation. Model Comparison Create choice information; include earlier probabilities and benefit frameworks. Information Source Tune models with normal squared slip or suitable benefit framework. Displaying Tools

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Assessment Tools Review Obtain implies and different insights on information source variables. StatExplore .:tslidese

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