Updated Wiki: RShelf

July 15, 2014, 12:18 am

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R Scripts "Shelf"

Here you'll find ready-to-go R Analytics which can easily be added to your R-enabled MicroStrategy environment.
If you can create a MicroStrategy metric then deploying R Analytics to MicroStrategy is simple.
No R experience is required.

Contents: (grouped by type of analysis, click on name to jump to that analytic)
Forecasting	Classification	Descriptive
ARIMA Seasonal Forecasting Stepwise Regression Survival Analysis New!	k Nearest Neighbors Neural Network Naive Bayes Random Forests Stepwise Logistic Regression	k-Means Clustering k-Medoids Clustering Pairwise Variable Correlation

These metric expressions work withR Integration Pack Version 2.
Click Here: For metric expressions that work with Version 1 (or any version).
Click Here: If you haven't already completed the installation steps.
Click Here: For details on how to deploy these analytics and use the new R Integration Pack Version 2 features.

R Analytic	Metric Expression (URL, Version 2)   [Switch to File]
Seasonal Forecasting One of the most common applications of predictive analytics is to forecast time-based data. This analytic uses R’s ordinary least squares regression algorithm to fit the best curve that captures the general trend and season variability of numeric data so it can use to predict future values. R Script Documentation Back to Contents	Forecast returns the forecasted value: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/SeasonalForecasting.R", _InputNames="Target, Trend, Season", _Params="FileName=''">(Target, Trend, Season)
ARIMA One of the most common applications of predictive analytics is to forecast time-based data. This analytic uses the Auto-Regressive Integrated with Moving Average (ARIMA) algorithm to project a sequence of values ahead into the future, based on the assumption that data points taken over time may have an internal structure that can be measured. While ARIMA tends to be esoteric and complex, this analytic uses the “auto.arima” function from R’s “forecast” package to search through a variety of possible models in order to find the best one. Not only does this script generate the expected forecast values, it also provides outputs based on confidence bands, nominally set at 80% and 95% confidence levels. R Script Documentation Back to Contents	Forecast returns the forecasted value: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/ARIMA.R", _InputNames="Target", SortBy=(Month), _Params="CycleLength=12, Horizon=12, Conf1=80, Conf2=95, ImageName='', FileName=''">(Target)
	ForecastLo1 returns the forecasted lower value of the first confidence band: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/ARIMA.R", _InputNames="Target", _OutputVar="ForecastLo1", SortBy=(Month), _Params="CycleLength=12, Horizon=12, Conf1=80, Conf2=95, ImageName='', FileName=''">(Target)
	ForecastHi1 returns the forecasted upper value of the first confidence band: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/ARIMA.R", _InputNames="Target", _OutputVar="ForecastHi1", SortBy=(Month), _Params="CycleLength=12, Horizon=12, Conf1=80, Conf2=95, ImageName='', FileName=''">(Target)
	ForecastLo2 returns the forecasted lower value of the second confidence band: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/ARIMA.R", _InputNames="Target", _OutputVar="ForecastLo2", SortBy=(Month), _Params="CycleLength=12, Horizon=12, Conf1=80, Conf2=95, ImageName='', FileName=''">(Target)
	ForecastHi2 returns the forecasted upper value of the second confidence band: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/ARIMA.R", _InputNames="Target", _OutputVar="ForecastHi2", SortBy=(Month), _Params="CycleLength=12, Horizon=12, Conf1=80, Conf2=95, ImageName='', FileName=''">(Target)
k-Means Clustering Using the K-Means algorithm, this analytic clusters records "by their nature" so that records within a cluster have more in common with each other than with those records in the other clusters. Each cluster is defined by a central point, it's "mean". R Script Documentation Back to Contents	Cluster returns the cluster to which the record belongs: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/kMeansClustering.R", _InputNames="Vars", _Params="Exact_k=4, Max_k=10, FileName=''">(Vars)
k-Medoids Clustering Using the K-Medoids algorithm, this analytic clusters records "by their nature" so that records within a cluster have more in common with each other than with those records in the other clusters. Each cluster is defined by a prototypical record, it's "medoid". R Script Documentation Back to Contents	Cluster returns the cluster to which the record belongs: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/kMedoidsClustering.R", _InputNames="Vars", _Params="Exact_k=4, Max_k=10, FileName=''">(Vars)
	Medoids returns the cluster if a record is the mediod of that cluster, 0 otherwise: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/kMedoidsClustering.R", _InputNames="Vars", _OutputVar="Medoids", _Params="Exact_k=4, Max_k=10, FileName=''">(Vars)
k-Nearest Neighbors k-Nearest Neighbors (kNN) is a simple classification technique that is unique in the sense that no model is explicitly trained. In the kNN process, two datasets are read in: the training dataset in which the dependent variable is already known, and the test dataset in which the dependent variable is unknown. Classifications for the test set are made by determining the k most similar records in the training dataset (known as neighbors) and returning the majority vote amongst those neighbors. R Script Documentation Back to Contents	Class returns the predicted class as a string: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/kNN.R", _InputNames="ID, Target, Training, Vars", _Params="TrainIncluded=TRUE, k=1, FileName='kNN'">(ID, Target, Training, Vars)
	ClassId returns the predicted class as a number: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/kNN.R", _InputNames="ID, Target, Training, Vars", _OutputVar="ClassId", _Params="TrainIncluded=TRUE, k=1, FileName='kNN'">(ID, Target, Training, Vars)
Naive Bayes Naïve Bayes is a simple classification technique wherein the Naïve assumption that the effect of the value of each variable is independent from all other variables is made. For each independent variable, the algorithm then calculates the conditional likelihood of each potential class given the particular value for that variable and then multiplies those effects together to determine the probability for each class. The class with the highest probability is returned as the predicted class. R Script Documentation Back to Contents	Class returns the predicted class as a string:/div> RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/NaiveBayes.R", _InputNames="Target, Vars", _Params="TrainMode=TRUE, FileName='NaiveBayes', Correction=1">(Target, Vars)
	ClassId returns the predicted class as a number: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/NaiveBayes.R", _InputNames="Target, Vars", _OutputVar="ClassId", _Params="TrainMode=TRUE, FileName='NaiveBayes', Correction=1">(Target, Vars)
Neural Network Neural Network is an advanced machine learning classification technique wherein a model is constructed that aims to simulate the thought process performed by the human brain. A model consists of “neurons” that are interconnected by an activation function. Every record is then passed through the network from the appropriate input neuron to the proper output neuron through a series of weights and transformations defined by the activation function. R Script Documentation Back to Contents	Class returns the predicted class as a string: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/NeuralNetwork.R", _InputNames="Target, Vars", _Params="FileName='NeuralNetwork', TrainMode=TRUE, NumLayer=3, Seed=42
	ClassId returns the predicted class as a number: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/NeuralNetwork.R", _InputNames="Target, Vars", _OutputVar="ClassId", _Params="FileName='NeuralNetwork', TrainMode=TRUE, NumLayer=3, Seed=42
Pairwise Variable Correlation PairwiseCorr measures the correlation between pairs of numeric variables to show how they behave with respect to each other. The primary output of this analytic is a correlation plot and a correlation table that contain the correlations of the variables when taken in pairs. R Script Documentation Back to Contents	Result returns "Ok" when the correlations were calculated with no errors: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/PairwiseCorr.R", _InputNames="Labels, Vars", _Params="HasLabels=TRUE, WindowSize=0, ImageName='PairwiseCorr', FileName='PairwiseCorr'">(Labels, Vars)
Random Forests Random Forest is an advanced classification technique wherein the training dataset is used to construct many independent decision trees. Every record is then passed into each individual decision tree for classification, and the class that is predicted by the majority of those decision trees is returned as the predicted class for that record. R Script Documentation Back to Contents	Class returns the predicted class as a string: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/RandomForests.R", _InputNames="Target, Vars", _Params="TrainMode=TRUE, FileName='RandomForest', NumTree=750, NumVar=3, Seed=42">(Target, Vars)
	ClassId returns the predicted class as a number: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/RandomForests.R", _InputNames="Target, Vars", _OutputVar="ClassId", BooleanParam9=TRUE, StringParam9="RandomForest", NumericParam1=750, NumericParam2=3, NumericParam3=42>(Target, Vars)
Stepwise Logistic Regression Stepwise Linear Regression is a variant on classical Linear Regression in which variables are only included in the model if they have a significant effect. R Script Documentation Back to Contents	Probability returns the predicted probability for each record: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/StepwiseLogissticRegression.R", _InputNames="Target, Vars", _Params="FileName='', Stepwise=TRUE">(Target, Vars)
Stepwise Regression Stepwise Linear Regression is a variant on classical Linear Regression in which variables are only included in the model if they have a significant effect. R Script Documentation Back to Contents	Forecast returns the predictions from the model: RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/StepwiseRegression.R", _InputNames="Target, Vars", _Params="FileName='StepwiseRegression', Stepwise=TRUE">(Target, Vars)
Survival Analysis Survival Analysis can be used to predict the probability of an event occuring, such as a component failure or a customer being lost. This analytic uses the Cox Regression algorithm to quantify the effect that each independent variable has on the likelihood that such an event will occur at some point in the future. R Script Documentation Back to Contents	Risk returns the risk of an event occurring relative to the average : RScript<_RScriptFile="http://s3-us-west-1.amazonaws.com/rshelf/Survival.R", _InputNames="Time, Status, Vars", _Params="TrainMode=FALSE, FileName=''">(Time, Status, Vars)

How to use:

These R Analytics are deployed to MicroStrategy as metrics by copying the metric expressions provided here into any MicroStrategy Metric Editor. The shelf includes metric expressions for Version 1 of the R Integration Pack as well as variations that take advantage of the new features in Version 2.

First, you'll have to decide how you want to access the R Script to be executed:

1. URL "On-the-Shelf":Metric Expression (URL) is the fastest way to get started for systems with internet connectivity is to access these R Analytics via the web (requires R Integration Pack Version 2 or higher).
2. File "Off-the-Shelf":Metric Expression (File) accesses these R Scripts using the file system. Just download and save theR Script to the Centralized RScripts Repository. Please note that each metric expression can also be found inside its R Script within the MicroStrategy header block at the top.

And Version 2 of the R Integration Pack makes it even simpler for end-users control the analytic's execution thanks to the_Params parameter that allows function parameters to be referenced by name using a string of name-value pairs. This is in addition to the original set of 27 pre-defined parameters (9 boolean, 9 numeric and 9 string).

After you've copied the metric expression for the analytic you wish to deploy:

1. Paste the Metric Expression into any MicroStrategy metric editor
2. Match analytic's inputs and function parameters for your application
3. Name and save the metric so it can be added to any MicroStrategy report, scorecard or dashboard

For details about how a particular analytic works, be sure to check out its Documentation.

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Share your scripts:

We'd like to encourage everyone in the community to use and share these R Scripts.  Have you written an R Script you'd like to share with the rest of the community? That would be great!

If you have a R Script you'd like to contribute, please email your script and it's documentation torpechter@microstrategy.com. We'll test it to confirm its ready for general use by others. Once accepted, we'll add it to this page.

Code Disclaimer:

This page provides programming examples.  MicroStrategy grants you a nonexclusive copyright license to use all programming code examples from which you can use or generate similar function tailored to your own specific needs.  All sample code is provided for illustrative purposes only. These examples have not been thoroughly tested under all conditions. MicroStrategy, therefore, cannot guarantee or imply reliability, serviceability, or function of these programs.  All programs contained herein are provided to you "AS IS" without any warranties of any kind. The implied warranties of non-infringement, merchantability and fitness for a particular purpose are expressly disclaimed.

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New Post: Compatibility Error Occured while running R code in MicroStrategy

July 28, 2014, 12:16 am

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Hi All,
I have created an RScript which is like this
twosam<-function(y1,y2){
x=2*(y1+y2);
x;
}
Its working fine in the RGui Console and verified when I paste this code via deployR() in creating new metric.But the data is not coming and error is logged in the error file which is given below
"Actual data type CLOSXP (3) is not compatible with expected data type double for output 'twosam'."
Please help me what Iam doing wrong and how to solve it asap.

New Post: Compatibility Error Occured while running R code in MicroStrategy

July 29, 2014, 10:24 pm

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Please Help Me..Its Important and I can't find any clue

New Post: Compatibility Error Occured while running R code in MicroStrategy

July 31, 2014, 1:35 pm

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Thanks for your question and sorry that you are having issues running your script.

It’s good that you have a function “twosam” that you wish to deploy to MicroStrategy. However, based on the code you’ve provided, all you have is a function created in R code. There’s nothing in your script that calls that function.

MicroStrategy treats the R Script as a black box with your code inside and MicroStrategy just needs to know how to pass data to that black box and consume the results from it. Unfortunately, It appears you are trying to return an R variable called “twosam” to MicroStrategy but twosam is a function (with an odd R data type CLOSXP). We pass data (scalars or vectors as numbers or text or booleans), not functions. This is all discussed in the R Integration Pack User Guide, see http://download-codeplex.sec.s-msft.com/Download?ProjectName=rintegrationpack&DownloadId=791498.

We would suggest modifying your script with three main changes (hopefully the comments added makes it clear what we’ve done and why):
1) We cleaned up your function code without changing its behavior
2) We added “Dual Execution Mode” so the code runs both in the R Console and the MicroStrategy environment (see page 17 of the User Guide)
3) We added code that actually calls your twosam function

twosam <- function(y1, y2) {   #twosam is a function that returns the doubled sum of two numbers 
  return(2*(y1+y2))
}

if(!exists("mstr.ExFlag")) {   #If this is NOT executed by MicroStrategy
  y1 <- 10                     #  Then set the y1 value for when this is run from the R Console 
  y2 <- 20                     #  Then set the y2 value for when this is run from the R Console 
}                              #  When run from the R Console, this will return 60 if y1=10 and y2=20

X <- twosam(Y1, Y2)            #Execute the twosam function

You should then use the deployR tool to capture the analytic’s signature (see page 26 of the User Guide) which will appear as this header block at the top of your script:

#MICROSTRATEGY_BEGIN
#
#RVAR Y1 -input -numeric -vector
#RVAR Y2 -input -numeric -vector
#
#RVAR X -output -numeric -vector  #Metric Expression: RScript<_RScriptFile="twosam.R", _InputNames="Y1, Y2">(Y1, Y2)
if(exists("mstr.WorkingDir")) setwd(mstr.WorkingDir)  #Working Directory if executed by MicroStrategy
#
#MICROSTRATEGY_END

Save the script with these changes to the RScripts folder. Then, to create a new metric that executes your R Script, paste into any metric editor the metric expression “RScript<_RScriptFile="twosam.R", _InputNames="Y1, Y2">(Y1, Y2)” and replace Y1 and Y2 with MicroStrategy metrics. When the new metric executes, MicroStratetgy will pass the data to your script, execute it inside R and consume the results.

Hopefully this makes sense. Good luck and please let us know how it goes!

New Post: Taking user input for R parameters

July 31, 2014, 2:07 pm

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To take a time parameter from an end-user, you have one challenge and two options:

The challenge is that we don't allow passing date/time data types between MicroStrategy and R, mainly due to the complexity involved with various date-time formats that can be used and the fact that most algorithms deal with dates and times as transformed numeric values (e.g., hours since midnight, day of week, months since 1/1/2000). The good news is that R has features such as the strptime and as.POSIXct functions which can handle a wide variety of data conversions to and from date/time formats (type "?strptime" and "?as.POSIXct" at an R Console command prompt for more details). You should be able to use these functions to convert numeric or string input from the end user into the required date/time object you need for your script.

You have two options for getting the input from the end-user:

• Use a function parameter: For scalar values, you can use a function parameter so the end user can edit the metric expression to set the value. Here's an example where the parameter StringParam1 contains the time input from the user: RScript<_RScriptFile="MyAnalytic.R", StringParam1="12/23/2013">(X, Y).
• Use a function argument: This also works for scalar values and users who can edit metric expressions using a static value as an input to the analytic; for example, RScript<_RScriptFile="MyAnalytic.R">(X, Y, "12/23/2013"). In addition, the argument could also take in a MicroStrategy metric that returned a scalar or a vector-- and if that metric contained a prompt, then the user would be prompted for the value.
  

Hope this helps, if not, please reply back.

Good luck!

New Post: Get Invalid Formula using MAD

July 31, 2014, 2:24 pm

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Sorry for the delay in responding. It's been a while... hopefully you've solved your problem by now.

If not, while it looks like your metric expression is correct syntactically (you have commas in all the right places, the <..>, [..], (..) all look correct), there are a couple other issues that would prevent the metric expression from validating:

• The RScript functions are not available in the project: While you installed the R Integration Pack, many MicroStrategy Analytics Enterprise users miss the step of running the configuration wizard to add the RScript functions to their project's metadata... but you're using MAD so that wouldn't apply.
• The names of the metrics don't exactly match.
  

Hope this helps, and good luck!

New Post: Multiple Outputs

July 31, 2014, 2:26 pm

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You create two metrics, both we the same metric expression except they specify different _OutputVar parameters.

New Post: Error "the formula for derived metric is incorrect"

July 31, 2014, 2:30 pm

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While I appreciate you believe you tried the above solution, which replaces Target in the metric expression with the name of an actual metric from your project, that error message indicates that you're still including Target in the metric expression. You have to replace Target with the name of the metric you want to forecast. Until you do, you will continue to get this error.

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New Post: Compatibility Error Occured while running R code in MicroStrategy

August 1, 2014, 2:10 am

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Thank you Sir,Now it works and I came to know what Iam doing wrong.Actually Iam new to MicroStrategy and R Analytics and I have assigned a task to create function in R and call it in MicroStrategy.I couldn't find any simple example in any pdf..Thank you once gain for your help.Hope you will help again.

New Post: Compatibility Error Occured while running R code in MicroStrategy

August 1, 2014, 2:24 am

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Can u suggest any good pdf or link in which R Analytic with MicroStrategy is given with basic examples that will be usefull to primer like me.

New Post: Compatibility Error Occured while running R code in MicroStrategy

August 1, 2014, 8:43 am

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Yes, of course.

First of all, there's the User Guide which is part of the installation and available any time from this website, just go to the Home or Documentation tab and CLICK HERE for the R Integration Pack User Guide. If you hadn't used this before, that would explain a lot of your confusion.

We also ship a sample R Script that's part of the installation, SeasonalForecasting.R. That script and other "Off-the-Shelf" R Scripts ready for you to deploy with complete documentation can also be found on this website, just go to the Home or Documentation tab and CLICK HERE for the R Script "Shelf" that contains ready-to-go R Analytics. If you hadn't seen these before, they should meet your needs.

Finally, on the MicroStrategy Corporate Site", you'll find two ½ hour video Webcasts on our R integration with more examples and tips: Part 1 for End-Users (installation/deployment) and Part 2 for R Developers.

Hope this helps, and good luck!

New Post: RScript functions help and syntax

August 1, 2014, 12:29 pm

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Hello everyone,

I have the metrics installed (and the schema refreshed), and I am able to build metrics and deploy R successfully. But I am not able to find the RScript metrics in the list of functions in Metric Editor. I am hoping to find the standard syntax used for all the variation of the RScript function (esp. RScriptAgg, RScriptsimple) but I cannot find anything on the metrics list or in the documentation here. Could someone please point me to the right direction? Sorry if I am missing something basic here.

Thanks,

New Post: RScript functions help and syntax

August 1, 2014, 1:49 pm

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This is covered in the User Guide on Page 8: "The R script functions are added to the list of Data Mining Functions available when creating metrics, including the functions RScript, RScriptU, RScriptAgg, RScriptAggU, and RScriptSimple."

These functions are stored in the Data Mining Functions folder, which maybe hidden in some interfaces (an exception is the MicroStrategy Developer metric editor). This is to discourage users from trying to build these metrics by hand since that can be a very error prone process. Instead, we provide other easier and more reliable ways to create metrics that implement these advanced analytics since they can have esoteric features that must be configured correctly in order to work properly. The logic at work here is to avoid giving users "enough rope to hang themselves."

For example, we have the Training Metric Wizard for creating metrics that build predictive models, because there's simply too many details for even the most expert user to get right when trying to build those metrics by hand. Similarly, since Predictive Metrics are either created automatically during report execution or via PMML Import, there's no need for users to build these by hand either.

The case with the RScript functions is similar and predicated on the fact that you must first have an R Script with the analytic's signature captured in the header block at the top of the R script before you can attempt to execute that R script from MicroStrategy. That header block includes the metric expressions to be used when creating metrics that execute that particular R script. Thanks to the deployR utility, the right function is automatically selected based on the nature of the variables used by the analytic and other settings you can control with that utility. Since it's important that the metric expression is consistent with the R Script and it's signature, it's always easier and more reliable to get the metric expression from the R script or the deployR utility.

I hope this makes sense. And please let me know if there's something you're trying to do where the current approach is sub-optimal for you.

New Post: Returning Graph or Chart created in R to MicroStrategy

August 6, 2014, 6:10 am

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Hi,
I have a question that is it possible to create a chart in R and display it in MicroStrategy Report..And what is a Sankey Report and how it can be created and to be displayed in MicroStrategy..
Thanks in Advance.

New Post: Returning Graph or Chart created in R to MicroStrategy

August 6, 2014, 8:39 am

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The data in MicroStrategy Reports can be viewed as a grid, graph or grid/graph using the MicroStrategy graph engines. To display a chart created using R (or any other source), instead use a MicroStrategy Document.

First, save the chart/graph/image from R as a file in the file system (JPEG, GIF, BMP, etc.). This post from R-Bloggers contains more details on how to do this: http://www.r-bloggers.com/automatically-save-your-plots-to-a-folder/.

Next, create a MicroStrategy Document and add an image/picture container to display the particular image file you saved in the step above, along side the report/grid that contains the metric which executes the R analytic used to create the image file. Any time you run the report, the image will be updated as the document is created.

A discussion of Sankey diagrams is a bit beyond the scope of this discussion forum, but a quick query using http://rseek.org/ revealed several packages and related posts that describe Sankey diagrams. For details on Sankey charts, see Wikipedia. And generating them using R is made easier thanks to packages like googleVis, riverplot and others.

Hope this helps, and good luck!

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New Post: reading PMML into MicroStrategy, latest version not supported

August 8, 2014, 7:17 am

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I created a predictive model using R and saved the result using the PMML package. but when I want to import the model into MSTR, I get the following error stating that the version of PMML (which is the latest version) is not supported.



I could not find the option to export PMML in a different version in the R package. Is there a way to do that? Is MSTR going to add an update for the latest version?

New Post: RScript functions help and syntax

August 8, 2014, 8:00 am

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Thank you for that thorough response. It makes sense not to show these to every user. I also usually use deployR to get the metric definition, it's a good utility and provides consistent and reliable results, but my inner geek wants to look deeper into these metrics.

I was hoping to get some more detail into the correct syntax and the proper intended use of each of these metric definitions, something like what we have for OLAP functions in the advanced reporting guide.

I understand RScript is for passing values between MSTR and R, and RScriptU is applicable for situations where the data is not to be sorted. I am still not 100% on what the intended use of RScriptAgg and RScriptSimple is.

New Post: reading PMML into MicroStrategy, latest version not supported

August 8, 2014, 12:11 pm

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Thanks for passing this along. We do have PMML 4.2 on our radar screen, nice to see demand for it. I cannot comment now as to when we will have support for PMML 4.2, but I can suggested a less-than-ideal workaround that could get you going in the meantime. The vast majority of PMML features in 4.2 are identical to the features of earlier releases that we do support. It could very well be that your PMML doesn't use or require a new PMML 4.2 feature at all. So, you could edit your PMML can manually lower the version number to 4.1 (and it's XSD reference, if any) and then try to import the PMML. If there does happen to be a 4.2 feature in the PMML that MicroStrategy cannot handle, you should see an error message with potentially useful information about exactly what feature is causing the problem. On the other hand, there's a good chance that your PMML does not use a feature MicroStrategy does not yet support and you'll have bypassed this basic version number check that preventing your PMML from being imported.

If you do give this a try, please respond back with your results.

Also, I would ask that you open a Tech Support case so we can track this issue and you'll get notified as to it's progress.

Thanks, and good luck!

New Post: Creating a digram using RCharts

August 25, 2014, 12:41 am

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I have written as script on R and save it in a file which goes like this

library(igraph)
library(rCharts)

g<-graph.tree(40,children=4)

E(g)$weight=1

edgelist<-get.data.frame(g)
colnames(edgelist)<-c("source","target","value")

edgelist$source<-as.character(edgelist$source)
edgelist$target<-as.character(edgelist$target)

sankeyPlot<-rCharts$new()

sankeyPlot$setLib("K:/R Script File/rCharts_d3_sankey-gh-pages/libraries/widgets/d3_sankey")
sankeyPlot$setTemplate("K:/R Script File/rCharts_d3_sankey-gh-pages/libraries/widgets/d3_sankey/layouts/chart.html")

sankeyPlot$set(
data=edgelist,nodeWidth=15,nodePadding=10,layout=32,width=960,height=500)

sankeyPlot$print(chartId="sankey1")

But when I run this code via calling Source R Code from file.It does not show the Sankey Chart instead it shows the javascript code in the console.After that when I write sankeyPlot on the console then the browser will open but show nothing..Please help me what Iam doing wrong and how can it be solve..Thanks in Advance.

New Post: Creating a digram using RCharts

September 4, 2014, 12:50 am

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library(igraph)
library(rCharts)

g<-graph.tree(40,children=4)

E(g)$weight=1

edgelist<-get.data.frame(g)
colnames(edgelist)<-c("source","target","value")

edgelist$source<-as.character(edgelist$source)
edgelist$target<-as.character(edgelist$target)

sankeyPlot<-rCharts$new()

sankeyPlot$setLib('http://timelyportfolio.github.io/rCharts_d3_sankey') #Changing the Library Path solved the problem
sankeyPlot$setTemplate(script = 'K:/R Script File/Sankey With RCharts/rCharts_d3_sankey-gh-pages/libraries/widgets/d3_sankey/layouts/chart.html')

sankeyPlot$set(

data=edgelist,nodeWidth=15,nodePadding=10,layout=32,width=960,height=500)

sankeyPlot

I have the library path and now it point directly to the github server and now the charts are working fine,but I still working on the previous error as if I have to set path locally.So Iam working on it and hope to solve it (God Willing).