Titlebook: Applied Advanced Analytics; 6th IIMA Internation Arnab Kumar Laha Conference proceedings 2021 The Editor(s) (if applicable) and The Author(

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書目名稱Applied Advanced Analytics影響因子(影響力)




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書目名稱Applied Advanced Analytics網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Applied Advanced Analytics被引頻次




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書目名稱Applied Advanced Analytics讀者反饋學(xué)科排名

instructive

Artificial Intelligence-Based Cost Reduction for Customer Retention Management in the Indian Life Ito a major cost head for life insurers. In this paper, the authors present an advanced analytic solution to effectively manage customer retention costs and improve the overall persistency. The paper demonstrates the use of several machine learning and deep learning neural network-based models to cla

Commentary

Mitigating Agricultural Lending Risk: An Advanced Analytical Approach,atures and gives a better prediction of a farmer going to default than the one built on features currently captured by banks. These additional variables give necessary insights into farmer characteristics that could (1) help banks identify low-risk farmers and expand their lending and (2) help the g

Condyle

Application of Association Rule Mining in a Clothing Retail Store,d in Indore, Madhya Pradesh, from the period November 26, 2017, to September 19, 2018, with the help of Point of Sale (POS) and bar code scanner. “Try Us” is a small retail store with multiple brands and is planning to upgrade store to a multilevel store. Data mining would benefit the overall store

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繁殖

Food Index Forecasting,lished by United States Department of Labor for the period January 2010 till May 2018. Different univariate and multivariate time series modeling approaches were used to model the price data, and best-fitted model was chosen for each of the individual categories.

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cognizant

Increment

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OTC Energy and Related Derivative Markets,rocesses of such applications. Due to the intense complexity of inherent structure of AI algorithm, usually researchers define the artificial neural network as “black box” whereas the traditional statistical learning models are more transparent, interpretable and explainable with respect to data and