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How to Mine Unstructured Data

In 2003, Information Management published a series of articles, starting with a missive titled “The Problem with Unstructured Data.”...

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Overview of Model Risk Control Operations

Easy availability of statistical tools, computational power and talent to build models has resulted in an explosion of models built by banks every year...

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Introduction to Probabilistic Topic Modeling

Probabilistic topic models are a collection of algorithms used to discover the hidden thematic structure in large archives of documents based on unsupervised

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Vector Autoregression

Vector auto regression (VAR) is an econometric model used to capture the evolution and the interdependencies between multiple time series models..

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Benchmarking of different programming languages

This paper details the procedure followed in choosing the programming language to be used for writing agents for agent based modelling(referred to as ABM in

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Predictability of Time Series

A statistical measure used to classify time series and infer the level of difficulty in predicting and choosing an appropriate model for the series at hand..

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Customer Purchase Behavior in the Airline Industry

This section begins with familiarizing the tools and technologies used. It gives a brief overview of the requirements and the system configuration...

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Constraint programming

Integer programming (IP) and mixed integer programming (MIP) have served the operations research (OR) community well for many years...

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Prediction using Kalman Filter

Kalman filtering was developed in the 1960s, although it has its roots as far back as Karl Gauss in 1795.

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Dynamic Linear Models

Dynamic linear models were developed in engineering in the early 1960's to monitor and control dynamic systems. Early famous applications have been in...

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