Titlebook: Business Analytics Using R - A Practical Approach; Umesh R. Hodeghatta,Umesh Nayak Book 20171st edition Dr. Umesh R. Hodeghatta and Umesha

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,The Gurov–Reshetnyak Class of Functions,(or discrete values), whereas regression and other models predict continuous valued functions. For example, a classification model may be built to predict the results of a credit-card application approval process (credit card approved or denied) or to determine the outcome of an insurance claim. Man

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https://doi.org/10.1007/978-94-017-6101-7 for in the company you want to invest in? Maybe the innovativeness of the products of the startups, maybe the past success records of the promoters. In this case, we say the profitability of the venture is dependent on or associated with innovativeness of the products and past success records of th

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https://doi.org/10.1007/978-94-017-6101-7te variable, you use a different regression method. If the response variable can take values such as yes/no or multiple discrete variables (for example, views such as strongly agree, agree, partially agree, and do not agree), you use logistic regression. You will explore logistic regression in a sep

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https://doi.org/10.1007/978-94-017-2223-0itutions have woken up to the value of data and are trying to collate data from various sources and mine it for its value. Businesses are trying to understand consumer/market behavior in order to get the maximum out of each consumer with the minimum effort possible. Fortunately, these organizations

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R for Data Analysis,nt concepts required for data analysis, including reading various types of data files, storing data, and manipulating data. We also discuss how to create your own functions and R packages. After reading this chapter, you will have a good introduction to R and can get started with data analysis.

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Preliminaries and Auxiliary Results,nt concepts required for data analysis, including reading various types of data files, storing data, and manipulating data. We also discuss how to create your own functions and R packages. After reading this chapter, you will have a good introduction to R and can get started with data analysis.

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