• Asia pacific journal of information systems
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• v.21 no.2
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• pp.43-58
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• 2011

Support vector machines (SVMs), a machine learning technique, has been applied to not only binary classification problems such as bankruptcy prediction but also multi-class problems such as corporate credit ratings. However, in general, the performance of SVMs can be easily worse than the best alternative model to SVMs according to the selection of predictors, even though SVMs has the distinguishing feature of successfully classifying and predicting in a lot of dichotomous or multi-class problems. For overcoming the weakness of SVMs, this study has proposed an approach for selecting features for multi-class SVMs that utilize the impurity measures of classification trees. For the selection of the input features, we employed the C4.5 and CART algorithms, including the stepwise method of discriminant analysis, which is a well-known method for selecting features. We have built a multi-class SVMs model for credit rating using the above method and presented experimental results with data regarding S&P 500 companies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.4881-4894
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• 2014

This study selected 83 manufacturing firms that had been delisted from the KOSDAQ market from 2009 to 2012 and the sample firms for the two-paired sampling method were compared with 83 normal firms running businesses with same items or in same industry. The 75 financial ratios for five years immediately before delisting were used for Mean Difference Analysis with those of normal firms. Fifteen variables assumed to be significant variables for five consecutive years out of the analysis were used to in the Dichotomous Classification Technique, Logistic Regression Analysis and Discriminant Analysis. As a result of those three analyses, the Logistic Regression Analysis model was found to show the greatest discrimination. This study is differentiated from previous studies as it assumed that the firm's failure proceeded slowly over long period of time and it tried to predict the firm's failure earlier using the five years' historical data immediately before failure, whereas previous studies predicted it using three years' data only. This study is also differentiated from the proceeding comparative studies by its statistically complex Multi-Variate Analysis and Dichotomous Classification Analysis, which general stakeholders can easily approach.

• Journal of Korean Academy of Nursing Administration
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• v.6 no.1
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• pp.135-146
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• 2000

The purpose of this study was to develope, based on the Nursing Intervention Classification (NIC) system. a set of standardized nursing interventions which had been validated. and their associated activities. for use with nursing diagnoses related to home health care for women who have had a caesarian delivery and for their newborn babies. This descriptive study for instrument development had three phases: first. selection of nursing diagnoses. second, validation of the preliminary home health care interventions. and third, application of the home care interventions. In the first phases, diagnoses from 30 nursing records of clients of the home health care agency at P. medical center who were seen between April 21 and July 30. 1998. and from 5 textbooks were examined. Ten nursing diagnoses were selected through a comparison with the NANDA (North American Nursing Diagnosis Association) classification In the second phase. using the selected diagnoses. the nursing interventions were defined from the diagnoses-intervention linkage lists along with associated activities for each intervention list in NIC. To develope the preliminary interventions five-rounds of expertise tests were done. During the first four rounds. 5 experts in clinical nursing participated. and for the final content validity test of the preliminary interventions. 13 experts participated using the Fehring's Delphi technique. The expert group evaluated and defined the set of preliminary nursing interventions. In the third phases, clinical tests were held at in a home health care setting with two home health care nurses using the preliminary intervention list as a questionnaire. Thirty clients referred to the home health care agency at P. medical center between October 1998 and March 1999 were the subjects for this phase. Each of the activities were tested using dichotomous question method. The results of the study are as follows: 1. For the ten nursing diagnoses. 63 appropriate interventions were selected from 369 diagnoses interventions links in NlC., and from 1.465 associated nursing activities. From the 63 interventions. the nurses expert group developed 18 interventions and 258 activities as the preliminary intervention list through a five-round validity test 2. For the fifth content validity test using Fehring's model for determining lCV (Intervention Content Validity), a five point Likert scale was used with values converted to weights as follows: 1=0.0. 2=0.25. 3=0.50. 4=0.75. 5=1.0. Activities of less than O.50 were to be deleted. The range of ICV scores for the nursing diagnoses was 0.95-0.66. for the nursing interventions. 0.98-0.77 and for the nursing activities, 0.95-0.85. By Fehring's method. all of these were included in the preliminary intervention list. 3. Using a questionnaire format for the preliminary intervention list. clinical application tests were done. To define nursing diagnoses. home health care nurses applied each nursing diagnoses to every client. and it was found that 13 were most frequently used of 400 times diagnoses were used. Therefore. 13 nursing diagnoses were defined as validated nursing diagnoses. Ten were the same as from the nursing records and textbooks and three were new from the clinical application. The final list included 'Anxiety', 'Aspiration. risk for'. 'Infant behavior, potential for enhanced, organized'. 'Infant feeding pattern. ineffective'. 'Infection'. 'Knowledge deficit'. 'Nutrition, less than body requirements. altered', 'Pain'. 'Parenting'. 'Skin integrity. risk for. impared' and 'Risk for activity intolerance'. 'Self-esteem disturbance', 'Sleep pattern disturbance' 4. In all. there were 19 interventions. 18 preliminary nursing interventions and one more intervention added from the clinical setting. 'Body image enhancement'. For 265 associated nursing activities. clinical application tests were also done. The intervention rate of 19 interventions was from 81.6% to 100%, so all 19 interventions were in c1uded in the validated intervention set. From the 265 nursing activities. 261(98.5%) were accepted and four activities were deleted. those with an implimentation rate of less than 50%. 5. In conclusion. 13 diagnoses. 19 interventions and 261 activities were validated for the final validated nursing intervention set.