Titlebook: Bankruptcy Prediction through Soft Computing based Deep Learning Technique; Arindam Chaudhuri,Soumya K Ghosh Book 2017 Springer Nature Sin

Coenzyme

书目名称Bankruptcy Prediction through Soft Computing based Deep Learning Technique影响因子(影响力)




书目名称Bankruptcy Prediction through Soft Computing based Deep Learning Technique影响因子(影响力)学科排名




书目名称Bankruptcy Prediction through Soft Computing based Deep Learning Technique网络公开度




书目名称Bankruptcy Prediction through Soft Computing based Deep Learning Technique网络公开度学科排名




书目名称Bankruptcy Prediction through Soft Computing based Deep Learning Technique被引频次




书目名称Bankruptcy Prediction through Soft Computing based Deep Learning Technique被引频次学科排名




书目名称Bankruptcy Prediction through Soft Computing based Deep Learning Technique年度引用




书目名称Bankruptcy Prediction through Soft Computing based Deep Learning Technique年度引用学科排名




书目名称Bankruptcy Prediction through Soft Computing based Deep Learning Technique读者反馈




书目名称Bankruptcy Prediction through Soft Computing based Deep Learning Technique读者反馈学科排名

陶醉

巧办法

Literature Review,univariate analysis in order to predict corporate bankruptcy. Neter [5] however strongly supported the use of multivariate analysis for this problem. Beaver discovered that till 5-year period before the organization’s failure, the number of ratios differed from corresponding non-failed organization.

Fresco

Bankruptcy Prediction,the number of business failures. There are four generic terms that describe corporate distress, viz., failure, insolvency, default, and bankruptcy, which form the backbone of corporate distress which ultimately leads to bankruptcy:

遗留之物

Need for Risk Classification,from the banks. Here no external rating is available. The banks use internal rating system to sketch the risk class to which the client belongs. The banks are given pressure from both sides by the Basel II. The risk premia is demanded by the banks with respect to the default probability of the speci

Affection

Conclusion,kruptcy database. FRTDSN-HRB performance is compared with fuzzy SVMs and other statistical models. To provide a balance in comparison, certain aspects that reduce or grow predictive accuracy are taken care through FRTDSN-HRB model. The cutoff points’ selection is affected by backcasting, choice-base

江湖郎中

reject

Bankruptcy Prediction through Soft Computing based Deep Learning Technique978-981-10-6683-2

Tincture

https://doi.org/10.1057/9780230612082s achieved through literature review and brainstorming the techniques. The literature review is presented in Chap. .. The methodology is highlighted in Chap. .. The appropriate data is collected to validate the chosen technique. The data preprocessing is performed with respect to the chosen techniqu

Absenteeism