By Subrata Das

Learn the right way to competently Use the most recent Analytics techniques on your Organization


Computational company Analytics provides instruments and methods for descriptive, predictive, and prescriptive analytics appropriate throughout a number of domain names. via many examples and not easy case stories from numerous fields, practitioners simply see the connections to their very own difficulties and will then formulate their very own resolution strategies.



The booklet first covers center descriptive and inferential statistics for analytics. the writer then complements numerical statistical suggestions with symbolic synthetic intelligence (AI) and computer studying (ML) thoughts for richer predictive and prescriptive analytics. With a distinct emphasis on equipment that deal with time and textual info, the text:





  • Enriches significant part and issue analyses with subspace tools, corresponding to latent semantic analyses

  • Combines regression analyses with probabilistic graphical modeling, corresponding to Bayesian networks

  • Extends autoregression and survival research innovations with the Kalman filter out, hidden Markov types, and dynamic Bayesian networks

  • Embeds choice bushes inside effect diagrams

  • Augments nearest-neighbor and k-means clustering ideas with help vector machines and neural networks



These ways aren't replacements of conventional statistics-based analytics; fairly, as a rule, a generalized strategy could be diminished to the underlying conventional base strategy less than very restrictive stipulations. The ebook exhibits how those enriched strategies provide effective suggestions in components, together with buyer segmentation, churn prediction, credits hazard evaluate, fraud detection, and ads campaigns.

Show description

Read or Download Computational Business Analytics (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) PDF

Similar data mining books

Robust Data Mining (SpringerBriefs in Optimization)

Information uncertainty is an idea heavily similar with so much actual lifestyles purposes that contain facts assortment and interpretation. Examples are available in facts received with biomedical tools or different experimental ideas. Integration of sturdy optimization within the current info mining strategies goal to create new algorithms resilient to mistakes and noise.

Data Mining Mobile Devices

With today’s shoppers spending extra time on their mobiles than on their desktops, new tools of empirical stochastic modeling have emerged which can supply dealers with distinctive information regarding the goods, content material, and providers their consumers hope. facts Mining cellular units defines the gathering of machine-sensed environmental facts relating human social habit.

Information Security Analytics: Finding Security Insights, Patterns, and Anomalies in Big Data

Info safeguard Analytics promises insights into the perform of analytics and, extra importantly, how one can make the most of analytic thoughts to spot developments and outliers that won't be attainable to spot utilizing conventional safety research concepts. details protection Analytics dispels the parable that analytics in the info safeguard area is restricted to simply defense incident and occasion administration structures and simple community research.

Big Data Analytics Using Multiple Criteria Decision-Making Models (Operations Research Series)

A number of standards choice Making (MCDM) is a subfield of Operations study, facing selection making difficulties. A decision-making challenge is characterised by way of the necessity to pick out one or a couple of between a couple of choices. the sector of MCDM assumes specific value during this period of massive facts and enterprise Analytics.

Additional info for Computational Business Analytics (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Example text

Download PDF sample

Rated 4.93 of 5 – based on 22 votes