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Dataset Evaluation for Statistical Learning and Data Mining Methods

Industry Consumer Goods and Retail

Specialization Or Business Function Market Research (Brand Perceptual Mapping, Brand Equity, Focus Groups, Sensory Research, Ethnography & Observational Research)

Technical Function Analytics, Ontology and Semantic Technology

Technology & Tools Big Data and Cloud, Machine Learning Frameworks

WORK IN PROGRESS

Project Description

Data evaluation
The dataset (
Pilot Project_SA170330) represents an extract of a greater data set which contains project data sets similar to the one presented here.


The task is to elaborate and evaluate which statistical learning and data mining methods would be appropriate to give insight into the hidden knowledge of the entire data set, provided that the other datasets are similar with respect to structure and quantity. Of special interest is if the data would allow association rule based learning. This includes the text data hence the data needs to be preprocessed with natural language tools in order to develop metrics for the text data that allow more sophisticated mining methods. 

Questions to be answered:

  • Can data mining methods provide valuable insight into the data and which methods would that be (e.g. clustering with dbscan with the following parameters...)? 
  • What can be expected with respect to the results? 
  • What would be the the costs (money and time)? 
  • If the data does not suffice the requirements of data mining what should be changed be different (structural problem, amount of data, etc.)?
  • What would be the cost for this evaluation (time, money)?
  • What additional data, when integrated with the dataset, would allow analyses and conclusions not possible with the additional data alone?

Project Overview

  • Posted
    March 27, 2017
  • Planned Start
    April 19, 2017
  • Delivery Date
    April 05, 2017
  • Preferred Location
    From anywhere

Client Overview


EXPERTISE REQUIRED

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