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Data Mining: Practical Machine Learning Techniques for CRM - HomeData Mining CRM: Machine Learning Techniques for Customer Relationship Management
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Data Mining CRM: Machine Learning Techniques for Customer Relationship Management
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Data Mining CRM: Machine Learning Techniques for Customer Relationship Management
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Getting Started: ARFF Files - Data Mining: Practical Machine Learning Techniques for CRM
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Data Mining: Practical Machine Learning Techniques for CRM. Getting Started: ARFF Files. Data mining platforms convert several data sources into a common data structure that allows an ecosystem of plug-in components to emerge and "speak a common language". In Weka machine learning, this common file format is called Attribute-Relation File Format. Or ARFF for short. Converting Salesforce Objects to ARFF: SObj2ARFF. Download and Build SObj2ARFF. Workspace/weka ./build.sh. Config file name/value pairs.
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Data Mining: Practical Machine Learning Techniques for CRM. Classifying Machine Learning Problems. When approaching CRM analysis using machine learning, it helps to first understand and categorize the problem. Each of the quadrants in the diagram below has it's own unique set of data collection and processing requirements. Problems result in labeling data. Problems result in making a numeric prediction, such as a probability. Opportunity Win/Loss (Batch Classification):. A call center may make make predi...
Classifying Machine Learning Problems - Data Mining: Practical Machine Learning Techniques for CRM
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Data Mining: Practical Machine Learning Techniques for CRM. Classifying Machine Learning Problems. When approaching CRM analysis using machine learning, it helps to first understand and categorize the problem. Each of the quadrants in the diagram below has it's own unique set of data collection and processing requirements. Problems result in labeling data. Problems result in making a numeric prediction, such as a probability. Opportunity Win/Loss (Batch Classification):. A call center may make make predi...
Welcome to Data Mining CRM! - Data Mining: Practical Machine Learning Techniques for CRM
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Data Mining: Practical Machine Learning Techniques for CRM. Welcome to Data Mining CRM! Begin With The End in Mind". Welcome to Data Mining CRM! This blog documents lessons learned applying various data science and machine learning techniques to Customer Relationship Management (CRM) data. Are my primary tools, both of which have free Developer tools available. Click on the " Resources. Page for links to the tools discussed in this blog. Developers, Analysts, Architects, Data Scientists, Statisticians; a...
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Embracing the Cloud - October, 2014
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Public String CloudThoughts{ get; set;}. Passion for building great solutions using cloud computing: Salesforce.com CRM, Force.com, Amazon Web Services, Heroku, Internet of Things. Full Archives By Category. October, 2014 (1). November, 2013 (1). October, 2013 (1). September, 2013 (1). January, 2013 (1). December, 2012 (1). November, 2012 (2). October, 2012 (1). July, 2012 (1). May, 2012 (1). October, 2011 (1). August, 2011 (1). May, 2011 (1). March, 2011 (2). February, 2011 (3). January, 2011 (1).
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Data Mining: Practical Machine Learning Techniques for CRM - Home
Data Mining: Practical Machine Learning Techniques for CRM. Classifying Machine Learning Problems. When approaching CRM analysis using machine learning, it helps to first understand and categorize the problem. Each of the quadrants in the diagram below has it's own unique set of data collection and processing requirements. Problems result in labeling data. Problems result in making a numeric prediction, such as a probability. Opportunity Win/Loss (Batch Classification):. A call center may make make predi...
Data Mining
Saturday, January 8, 2011. Scoring Association Rules - You Must Know. At M2009 (SAS's data mining conference), I was approached with the question of scoring association rules for customers. This is not a topic I have thought about very much. More typically, association rules are used qualitatively or to understand products. I hadn't thought about assigning the "best" rule (or rules) back to customers. Using SQL and Excel. However, data mining tools do not provide the ability to score association rules fo...
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