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This personality pattern is characterized by a passively independent orientation, noted by a self-image of superior worth, often learned in response to admiring and doting parents. Providing self-rewards is highly gratifying, if the individual possesses either a real or an inflated sense of self-worth. Displaying manifest confidence, arrogance, and an exploitive egocentricity in social contexts, this self-orientation has all that is important himself or herself. The four subtypes of the narcissist include the elitists, who fancy themselves as demigods, flaunt their status, and engage in self-promotion. Other variants are the compensatory type with covert avoidant features, underlying feelings of inferiority, but public displays of superiority. Noteworthy also are the amorous and unprincipled subtypes.
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Distributed Database Management Systems by Saeed K. Rahimi and Frank S. Haug Copyright 2010 the IEEE Computer Society
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4. Press the Choose button, next to classi er. 5. Select Classi ers Bayes Naive Bayes from the navigation hierarchy. 6. Click OK to close the WrapperSubsetEval dialog. The evaluation method for AttributeSelection is now speci ed. 7. On the AttributeSelection dialog, press the Choose button next to search. 8. Select AttributeSelection GeneticSearch from the navigation hierarchy. 9. Press OK to close the AttributeSelection dialog. The evaluator and search methods for attribute selection have been speci ed; however, our changes haven t yet been applied to our data set. 10. Press the Apply button on the right side of the Explorer panel. After processing the command, WEKA displays updated results in the Explorer panel. In particular, under Attributes, notice the list now shows seven predictor attributes. That is, the two attributes single-cell-size and mitoses have been removed from the attribute list. Let s reclassify the records using naive Bayes with 10-fold cross-validation; however, this time only seven attributes are input to the classi er. 1. Select the Classify Tab. 2. Under Classi er, press the Choose button. 3. Select Classi ers Bayes Naive Bayes from the navigation hierarchy. 4. Cross-validation is speci ed. 5. Click Start. Now, naive Bayes reports 96.78% (661/683) classi cation accuracy, which indicates that the second model outperforms the rst model by almost 0.05% (96.78% versus 96.34%). That is, classi cation accuracy has increased where only seven of the nine attributes are speci ed as input. Although these results do not show a dramatic improvement in accuracy, this simple example has demonstrated how WEKA s Genetic Search algorithm can be included as part of an attribute selection approach. Let s further examine the results reported by WEKA s Genetic Search method, where the characteristics of the candidate population are described. The following procedures should look similar to those performed above. This time, however, we re invoking the attribute selection lter from WEKA s Select attributes Tab, which provides detailed output. 1. Return to the Preprocess Tab on the Explorer panel. 2. Press the Undo button (top right). This removes the lter we applied to the data set earlier. 3. Select the Select attributes Tab from the Explorer panel. 4. Under Attribute Evaluator, press the Choose button. 5. Select AttributeSelection WrapperSubsetEval from the navigation hierarchy. 6. Click on the text WrapperSubsetEval . . . to open the WrapperSubsetEval dialog.
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15: Structuring Lines and Paragraphs with Block-Level Elements . . . . . . . . . . . . . . . . . . . . 179
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OTHER OBJECTIVE TESTS: Additional objective personality tests include the Edwards Personal Preference Schedule (EPPS: A. L. Edwards, 1959), a 225-item paired-comparison test assessing 15 personality variables, and the Eysenck Personality Questionnaire (Eysenck & Eysenck, 1975), measuring three basic personality characteristics: psychoticism, introversion-extroversion, and emotionalitystability. Many other tests are available as well, however, they generally are not as commonly used as those previously discussed.
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MemoryStick is a nifty free utility (Matt Neuberg, www.tidbits.com/matt) that lets you keep an eye on memory usage in your Mac. MemoryStick, pictured in Figure 7-8, is designed to provide an unobtrusive monitor on various aspects of OS X virtual memory management.
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We can nd an n such that 2 (n 1) > pi 2 n , or n 1 < log pi n. Then it follows that pi as
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