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There are three qualities related to data mining methods that should be evaluated when selecting methods: Absence of restrictive assumptions Capacity to complete analysis of the data within a reasonable time (processing power) Possibility of handling incomplete and heterogeneous data Thanks for following my blog, there’s more to come.
When it comes to predictive methods there are more aspects to consider. In this post I’ll cover several of them. Many of these distinguishing characteristics are related to the differences in the variables; independent (in rows) and dependent (in columns). Rows (independent variables) with quantitative and qualitative data are only relevant if the columns (dependent variables) correlate with each … Read moreData Mining Methods, Part 2 – Predictive methods
In data mining and data analysis it may seem like there are a hundred bits of info to remember about the methods and techniques… well, maybe there is. So I’m going to try to organize it a little bit. Data mining and data analysis methods can be divided into two large groups: descriptive methods and predictive … Read moreData Mining Methods, Part 1 – Classification
One of the most popular statistical software tools is R. However, just because it’s popular doesn’t make it the best choice for every problem. Looking at how the software handles large datasets, ease of access to different databases, simplicity of deployment and ease in handling automation are also important. Just something to keep in mind … Read moreStatistical and Data Mining Software
In this post I’ll describe some of the data that is used in commercial data mining. This data may be aggregated to some level or kept at the individual level, depending on the aim of the study and the methods available. Often commercial transactions are of particular interest, especially in studies on consumption. In these … Read moreUsing Commercial Data in Data Mining
The Different Types of Data Quantitative, qualitative, or textual; what the heck? Quantitative is just a big word for measurable. Most numerical data falls in to this type of data; things like the age or income of customers and the weight of trucks going through a port of entry. Within this type there are two … Read moreData Exploration and Preparation
“I love it when a plan comes together!” – John Smith 1928 – 1994 Before a plan can come together, you have to make one. Here are some key points to consider during development of a data mining study. Defining the aims Start by choosing the subject and relevant aspects (customers, widgets or potatoes) Give … Read moreDevelopment of a Data Mining Study
What was formerly confined to the lab and the socially awkward in white coats has found its way in to a range of areas. These areas ranging from the very small (genomics) to the infinitely large (astrophysics) and from the mundane (customer relationship management) to the very specialized (aviation assistance for pilots). Data mining has … Read moreOverview of Data Mining
Sometimes I wonder if I have ever stopped learning. I seems like a never-ending task, one without end or completion. I’ve decided that while this is true, it doesn’t have to be something that must be endured. In fact, it can be quite rewarding; both the process of learning and possession of knowledge. I’ve been … Read moreData Mining and Analytics… how exciting