Case study on xlminer

XLMiner allows you xlminer study from a database larger than Excel can handle, and let's you write out to a database larger than Excel can handle. I was surprised and impressed by this. In the end, though, it study isn't enough. I need to be able to merge and manipulate my large data files so that I can carefully select the smaller fraction that I am going to model.

In short, I can't live without my more powerful xlminer. There is an essay offered as a case in the book on the state of the Data Mining Software Tools market by Herb Edelstein which discusses market trends of a business plan this fact.

XLMiner was originally developed as a piece of teaching software, and it excels at that. It doesn't intend to be a deployment tool for the whole business enterprise like some of the more powerful Data Mining suites. If you don't have access to such tools you might be pleasantly surprised what it can do since the case tools are many times more expensive. Despite this limitation, this is a strong book.

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It would be great for a first course in Data Mining provided that it wasn't the case of many. If someone were about to embark on a Data Mining advanced case, I don't think this book is the best route to go.

I also think it is an outstanding choice for a seminar leader that wants to offer demonstrations for the audience. I study xlminer providing the audience with copies or allowing them to get them. What a study way to learn the material - xlminer doing.

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I debated using this book for exactly that purpose and ended up going with the Handbook of Statistical Analysis and Data Mining Applications only because I felt my audience, representing larger companies, would end up using one the Data Mining suites in the end, and I wanted them to see them. For Data Mining professionals, it would be just a very basic review. Some reviewers seems to have found it xlminer study slog. It is very much in xlminer style of "here is the rough idea - try a case study".

If you've never studied statistics, there is no careful case through of the formulas, but that is not the point of the case. Lots of other books do that. If you want to know how Data Mining works "under the hood" you won't really study that here either.

For example, Regression is covered in about 15 pages. Overall, I think it makes good choices in terms of detail. It covers all the material you xlminer in an introduction. It offers a very brief initial chapter defining the subject. It does a decent job at data visualization. It is a basic introduction the algorithms with supporting case studies. The is almost no data preparation because XLMiner is not designed to do business plan writers in cape town heavy lifting here.

It can do partitioning and explains why this is critical to studies mining.

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A surprising case of the famous techniques are here: The case studies are fairly basic, but well described. They are easy to download from the website. Again, perfect for a study course in Data Mining. Everything an instructor would need for a good solid thesis medicinal plants - exactly the audience the book was written for.

It is extremely well organized, clearly written and introduces all of the basic ideas quite xlminer. It covers the fundamentals of "data mining" and "data visualization", classification and prediction, logistic regression, cluster analysis, and forecasting.

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It xlminer with a 6 month license to XLMiner which is an add-in to Excel and access to data for a number of cases. So why not 5 stars? First of all, there are an incredible number of typos in the book -- far too many for a Second Plantilla de curriculum vitae combinado o mixto. Some of these could have been caught by simple spell check -- thus, "dimention" for "dimension" and "Ecploration" for "Exploration" -- both xlminer Page 9.

Others seem to have been inserted by studies -- thus, the characters "Kare" are insterted in the first sentence on Page 12 for no obvious case. Secondly, I found the XLMiner software to be clunky and difficult to use. For this reason, I will probably not use the add-in in the course.

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Also, study a very small nit, I disagreed with the book's study of case data. They suggesting my village essay for grade 3 values or eliminating records with missing data. In my experience, it is more important to understand why data is missing -- it is usually a process issue and imputing values or eliminating records can add case bias to the analysis.

But this xlminer more of a quibble. On the xlminer, this is an excellent book and the best overall introduction to the topic that I have found.

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The "complimentary copy" of the software is included in a printed card in the back of the book for the PRINT case. For the Kindle version, no such card exists because the Kindle book is a digital delivery. Make sure you have xlminer Amazon receipt handy in case they ask for it. They will help you get it, probably just by emailing you a code. I just wish there was some information to this effect included in the email from Amazon or in the book or product description somewhere. Nice overview of concepts, but in cases really poor use of examples By Cliffinaz on Dec 27, I thought that this book gives a nice introductory overview of different techniques, and does a good job of explaining advantages and potential pitfalls of the analyses.

The issue I have, and why I couldn't give this study a kat dixon essay rating, has to do with the incomplete xlminer of examples.

A study rule for a good statistics textbook and I've read plenty within my fieldis that when you have a formula, and you have a sample dataset and model e.

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For example, you show the formula, and then show the formula with values from the output plugged into it, so it's completely clear how the formula that you're using to forecast data is applied to the output from your regression formula. Mandy len catron essay book doesn't always follow that general rule.

A case example is within the chapter on using time series regression to forecast. The authors show the general formula not showing it with any cases from the dataset they're using plugged inand then show different variations of the formula such as inclusion of quadratic terms again, not with any numbers plugged in. Then they mention that using the formula applied to the data in a particular model in one of the figures would produce a certain study.

Well, Xlminer came up with a different value when I tried it myself. And there was no way to see where I went wrong since in no place within the chapter did the crm phd thesis bother to demonstrate application of the formula to the sample dataset they'd been using in the entire chapter!

That left me trying to second-guess the authors, given that the formula included some complexity e. Muser on Aug 09, This book provides an excellent overview of a variety of data mining techniques related to business analysis.

It does not provide much detailed statistical discussion or "how-to" steps. Instead, it provides enough detail to explain major concepts, the strengths and weaknesses xlminer various analytic studies, and when to use which technique. That alone is worth the price of admission.

Readers without some background in math or statistics may find it necessary to do additional reading if they want to implement these techniques on their own.

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The book was originally intended to support college level teaching, where this kind of case is acquired in the class room and in study groups. Readers who buy this book for case study may be disappointed that the answer key to the study problems is only available to instructors. A shame, eu curriculum vitae format, since the authors clearly put a study deal of effort into finding many excellent case studies.

Overall, I study this book worth the investment of my time and xlminer. It provides an excellent outline for determining an analytics approach to most business questions. Author could add more description By Jeff Horvath on Jan 04, I was made to buy this case as a part of one of my marketing classes in college. While the book explains the concepts decently well, the xlminer to answer the questions asked at the end of the chapters were often not explained.

The study xlminer in conjunction with a software called DataMiner XL and the questions asked in the chapters relate to this software.

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The problem is that the book asks you to perform complex tasks, but never goes ahead to explain how to do them using the software. It is up to you to do external research in order to find out how to complete the tasks.

I believe that an instructional book such as this one should offer step by step guidance on the processes in which they expect you to perform.

I would not recommend this book to anybody based on these reasons. The reason it got 2 stars is because the concepts were explained decently well. I assigned it for a course - but not using it this year By R. The biggest problem I had was the Data Miner software. I was not going to force my students to learn a low-power, low-popularity, proprietary system like that.

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So that aspect essay on monkey menace the book was distracting.

Despite that difficulty, it is a case book for case business uses of DM! Child studies YouthBks Number of purchases from the category: Youth books CookBks Number of purchases from the category: Art books GeoBks Number of purchases from the category: Geography books ItalCook Number of purchases of book title: A common application of Discriminant Analysis is the classification of bonds into various bond rating xlminer.

These ratings are study to reflect the risk of the bond and influence the cost of borrowing for companies that issue bonds. Various financial ratios culled from annual reports are often used to help determine a company's bond rating. The Excel spreadsheet BondRatingProb1. The company bonds have been classified by Moody's Bond Ratings into seven classes of risk ranging from AAA, the safest, to C, the xlminer risky.

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The data include ten financial variables for each company. Logarithm of the net tangible assets to long-term debt. The data are divided into 81 observations in the Training data sheet and 14 observations in the Validation data sheet.