Experience accurate machine learning and predictive outputs
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Very powerful and easy to use. The user has a lot of control over parameter settings, which is not available in other packages I use (both commercial and freeware). Since you have more control, you are able to get better results than other packages without risking overfitting.
Some users may not like the older style GUI, but most experts I know appreciate the simple interface since it runs faster and does not hog system resources.
Buyer Behaviour predictions, fraud prediction, market segmentation.
Ready-to go data mining and prediction tool, very robust and easy to import data. Very high performance
It's well liked by everybody I know of. Beginners and power users.
I recommend it highly, as a standard and for comparisons with other analysis and code implementations, e.g. for the same algorithms.
Any predictions, inference and data mining. We use it to pre-screen data and then to finalize an analysis.
Precision predictive tool for the development of automation models based on data and data sets that will improve your organization as such, the nature of and predictive analysis methods are excellent for improving the scenario. When you want to obtain specific information for the analysis, you must extract the data and understand them.
After completing the entire process, prepare the documentation, as well as make use of the special functions of the program, then you can see particular results with specific summaries and in a unified way.
SPM, gives you the possibility to select the file you want to open, and convert it into the formats that we use daily and others.
I do not have anything negative to limit, just with having knowledge in Database, you can establish the predefined formats and import them into this program. If you use compatible formats, reading data is easy, you must take into account to have a successful import we must respect certain parameters which each extension will give you the conversion of variables.
If you are going to invest in this program, I recommend a good induction to the staff that will carry out and interact with it daily.
A good program which has established a good mechanism to streamline daily work, the capacity for development and analysis is very good.
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SPM is an exceptionally good tool for making predictions.
1) The user interface is both menu driven (for exploratory use) and also programatically driven (for highly efficient production.) The menu-system produces as output the corresponding program for saving, improvement, and reuse.
2) There is an exceptional data cleaning and exploratory toolkit (much better than standard tools like SAS's PROC FREQ). Well thought-out. Data cleaning is extremely important, even in data mining, to understand the many nuances, histories, and biases of the data.
3) To make economically-optimal decisions requires optimizing the error costs. You cannot simply minimize the total Type 1 and Type 2 error rates (or related functions like Somers' D or Gini) as the costs of the errors can be vastly different. SPM's CART is a fabulous program in that it enables this extremely important optimization.
4) The main tool of SPM is TreeNet--their Stochastic Gradient Boosting algorithm. TreeNet is genuinely exceptional. It allows efficiently exploring a rich family of algorithmic options. In particular it has a sophisticated way to explore the required interaction structure.
5) The Partial Dependency Plots are easy to produce and explore and enable developing an intuition for the general behavior of the predictions. You can then spline these plots (with monotonicity if so desired), put those new basis functions back into the fit, and end up discovering a set of simultaneous optimal transformations. This is not possible to do with any univariate tool.
6) The scoring code can be output in numerous languages and thus easily deployed in diverse production environments.
7) The additional data mining algorithms (Random Forests, Multiple Adaptive Regression Splines, and more) are well implemented and at times give additional views into the corners of your predictions.
SPM is absolutely the top-of-the-line of powerful, easy to use, flexible, reliable, data mining software. It is the standard that pretty much everyone is always comparing to and against.
I have brought it into multiple companies and everywhere it has been readily adopted by both the advanced predictive modelers as well as by the skilled business analysts.
I hope that the new owners of SPM (Minitab) continue to invest in the development of SPM. I have heard of some very nice new ideas that will make SPM still better.
Most recently I have been been modeling consumer behavior in US banking. This involves responsible use of credit, retail price sensitivity, and responsiveness to direct and internet advertising. I have been using Bayesian Sequential Experimental Designs (along the lines of Thompson Sampling) to continually (re)evaluate the optimal set of treatments to be applied to every individual.