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Oracle Named a Leader in the 2017 Gartner Magic Quadrant for Enterprise Integration Platform as a Service

Oracle Press Releases - Fri, 2017-04-07 14:22
Press Release
Oracle Named a Leader in the 2017 Gartner Magic Quadrant for Enterprise Integration Platform as a Service Oracle positioned as a leader based on ability to execute and completeness of vision

Redwood Shores, Calif.—Apr 7, 2017

Oracle today announced that it has been named a leader in Gartner’s 2017 “Magic Quadrant for Enterprise Integration Platform as a Service” report1. We believe this recognition is another milestone which the company feels is due to the tremendous momentum and growth of Oracle Cloud Platform this year.

“We believe this recognition is another acknowledgement of Oracle’s strong momentum in the integration and larger PaaS sector, driven by the successful adoption of Oracle’s cloud platform offerings by thousands of customers,” said Amit Zavery, senior vice president, Oracle Cloud Platform and Middleware. “By successfully delivering a comprehensive iPaaS offering that provides an easy way to integrate any type of application, data, device and system, Oracle has given customers a powerful option to meet their ever evolving integration needs.”

Gartner positions vendors within a particular quadrant based on their ability to execute and completeness of vision.  According to the report, “leaders in this market have paid client numbers in the thousands for their iPaaS offerings, and often many thousands of indirect users via embedded versions of the platform as well as "freemium" options. They have a solid reputation, with notable market presence and a proven track record in enabling multiple integration use cases — often supported by the large global networks of their partners. Their platforms are well-proven and functionally rich, with regular releases to rapidly address this fast-evolving market.”

Oracle Cloud Platform, which includes Oracle’s iPaaS offerings, has experienced explosive growth, adding thousands of customers in fiscal year 2017. Global enterprises, SMBs, and ISVs are turning to Oracle Cloud Platform to build and run modern Web, mobile, and cloud-native applications. Continuing its commitment to its customers, Oracle has delivered more than 50 cloud services in the last two years.

Gartner views integration platform as a service (iPaaS) as providing “capabilities to enable subscribers (aka “tenants”) to implement data, application, API and process integration projects spanning cloud-resident and on-premises endpoints.” The report adds, “This is achieved by developing, deploying, executing, managing and monitoring “integration flows” (aka “integration interfaces”) — that is, integration applications bridging between multiple endpoints so that they can work together.”

Oracle’s iPaaS offerings include Oracle Integration Cloud Service and Oracle SOA Cloud Service, both part of the Oracle Cloud Platform. Oracle Integration Cloud is a simple and powerful integration platform targeting ad hoc integrators while Oracle SOA Cloud delivers a high-control platform for specialist integrators. Additionally, Oracle has many other cross-PaaS offerings that can be combined with Oracle’s iPaaS services to deliver greater productivity.  Those services include Oracle Self Service Integration for citizen integrators, Oracle Process Cloud for improved orchestration, Oracle Real-Time Integration Business Insight for business activity monitoring, Oracle API Platform Cloud for API management, Oracle Managed File Transfer Cloud for managed file transfer and Oracle IoT Cloud for IoT integration.

Download Gartner’s 2017 “Magic Quadrant for Enterprise Integration Platform as a Service” here.

Oracle Cloud

Oracle Cloud is the industry’s broadest and most integrated public cloud, offering a complete range of services across SaaS, PaaS, and IaaS. It supports new cloud environments, existing ones, and hybrid, and all workloads, developers, and data.  The Oracle Cloud delivers nearly 1,000 SaaS applications and 50 enterprise-class PaaS and IaaS services to customers in more than 195 countries around the world and supports 55 billion transactions each day.

For more information, visit http://cloud.oracle.com.

Gartner Disclaimer
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

1 Gartner, “Magic Quadrant for Enterprise Integration Platform as a Service,” by Keith Guttridge, Massimo Pezzini, Elizabeth Golluscio, Eric Thoo, Kimihiko Iijima, Mary Wilcox, March 30, 2017

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About Oracle

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Trace files segmented in multiple parts as a workaround for bug 23300142

Yann Neuhaus - Fri, 2017-04-07 12:27

Today I visited a customer, who deleted a Data Guard configuration (i.e. a temporary Data Guard setup through the broker was deleted). The LOG_ARCHIVE_DEST_STATE_2 on the primary database was set to DEFER temporarily. That resulted in trace-files with name *tt*.trc to become huge (GBytes after a couple of days). Analysis showed that this was caused by bug 23300142 in See My Oracle Support Note

Bug 23300142 - TT background process trace file message: async ignored current log: kcclenal clear thread open (Doc ID 23300142.8)

for details.
Unfortunately the bug does not have a workaround.
Due to the fact that the affected development-databases (which were now normal single instances without Data Guard) could not be restarted, I searched for a temporary workaround to stop the trace-files from growing further. Limiting the trace-file size on the database with

alter system set max_dump_file_size='100M';

did actually not always work to limit the file size. Here an example of a huge trace file (over 5GB):

$ find . -name "*tt*.trc" -ls | tr -s " " | cut -d " " -f7-11 | sort -n
5437814195 Apr 7 10:46 ./xxxxxx_site1/XXXXXX/trace/XXXXXX_tt00_28304.trc

However, what came in handy was the uts-trace-segmentation feature of 12c. See Jonathan Lewis’ blog here:


I.e. I left all DBs on max_dump_file_size=unlimited and set

SQL> alter system set "_uts_first_segment_size" = 52428800 scope=memory;
SQL> alter system set "_uts_trace_segment_size" = 52428800 scope=memory;

Unfortunately setting the limit to the tt-background-process alone does not work:

SQL> exec dbms_system.set_int_param_in_session(sid => 199, serial# => 44511, parnam => '_uts_trace_segment_size', intval => 52428800);
BEGIN dbms_system.set_int_param_in_session(sid => 199, serial# => 44511, parnam => '_uts_trace_segment_size', intval => 52428800); END;
ERROR at line 1:
ORA-44737: Parameter _uts_trace_segment_size did not exist.
ORA-06512: at "SYS.DBMS_SYSTEM", line 117
ORA-06512: at line 1

With the default setting of “_uts_trace_segments” (Maximum number of trace segments) = 5 I could limit the maximum size of the trace of 1 DB to 250MB (50MB * 5). Below you can see only 4 files, because of 2 tests with earlier splittings of the trace-file:

$ ls -ltr *_tt00_28304*.trc
-rw-r----- 1 oracle dba 52428964 Apr 7 14:14 XXXXXX_tt00_28304_3.trc
-rw-r----- 1 oracle dba 52428925 Apr 7 16:07 XXXXXX_tt00_28304_4.trc
-rw-r----- 1 oracle dba 52428968 Apr 7 17:12 XXXXXX_tt00_28304_5.trc
-rw-r----- 1 oracle dba 43887950 Apr 7 18:50 XXXXXX_tt00_28304.trc

The feature of segmented trace-files may help a lot in situations like bug 23300142.

REMARK: Do not use underscore parameters in production environments without agreement from Oracle Support.


Cet article Trace files segmented in multiple parts as a workaround for bug 23300142 est apparu en premier sur Blog dbi services.

Data Lake and Data Warehouse

Dylan's BI Notes - Fri, 2017-04-07 11:23
This is an old topic but I learned more and come up more perspectives over time. Raw Data vs Clean Data Metadata What kind of services are required? Data as a Service Analytics as a Service Raw Data and Clean Data I think that assuming that you can use raw data directly in a dangerous thing. […]
Categories: BI & Warehousing

Can I have only two editions using Oracle EBR for my application and still achieve zero downtime?

Tom Kyte - Fri, 2017-04-07 09:06
Hi Tom, We are planning to implement Oracle EBR in our DB and plan to have only two editions created ED1 and ED2 apart from ORA$BASE. We would also ensure that all the 5000 objects(editionable) we have in ORA$BASE would be actualized into ED1 and ...
Categories: DBA Blogs

How to update tables in loop having 5L records in each table effectively in less time

Tom Kyte - Fri, 2017-04-07 09:06
Hi Tom, i have a scenario where i need to update so many tables(around 80) at once and each table having a minimum of 5 Lakhs records and i used below approach. it is taking more time(don't know exactly because it is still running from more than ...
Categories: DBA Blogs

ORA-00838: Specified value of MEMORY_TARGET is too small

Tom Kyte - Fri, 2017-04-07 09:06
Categories: DBA Blogs

First Date of Week(Monday Date)

Tom Kyte - Fri, 2017-04-07 09:06
Using PO_DT field in Oracle, Trying to get the First Date of week based on value of PO_DT.
Categories: DBA Blogs

continuous scrolling output for table data

Tom Kyte - Fri, 2017-04-07 09:06
hi tom, I am a big fan of your work. We are in need of a procedure, which gives output of table data in ... tail -f format ... meaning the output is continuous, never ending procedure that shows records as it happens in table. I am looking to ha...
Categories: DBA Blogs

Default column value vs commit write batch nowait. When actual value is assigned?

Tom Kyte - Fri, 2017-04-07 09:06
Hi Tom, <b>In this section I'll explain how I come up with the question..</b> Under normal operation, our application do next actions: 1. call util.do_some_action, but not wait for response 2. do some network calls to remote system 3. receiv...
Categories: DBA Blogs

swingbench datagenerator connect string

Tom Kyte - Fri, 2017-04-07 09:06
I need to use [swingbench][1] to quantify performance of a given host. However since I am pretty new to Databases as such cannot get the [datagenerator][2] program to connect to an Oracle DB instance that has been "opened" on the host. After insta...
Categories: DBA Blogs

How to trace plsql executed by a package or a procedure

Tom Kyte - Fri, 2017-04-07 09:06
Hi, In an application that we use (which uses Oracle as the database to store data), when we update and save data, it internally calls a plsql package or a procedure to invoke an UPDATE statement. We have traced the UPDATE statement using db le...
Categories: DBA Blogs

Using package global variables

Tom Kyte - Fri, 2017-04-07 09:06
We are trying to do some conversion of large tables (100 mil rows) in 11g. This is a vendor based schema so from existing structure to new structure with some calculations involved. Our developers want to use package global variables. I heard it is r...
Categories: DBA Blogs

Compare two tables having different data types and different column name

Tom Kyte - Fri, 2017-04-07 09:06
HI Tom, I have two table in migration , source table and destination table.. Column Names in source table are different w.r.to destination table and data type is also different but Fields are mapped from source table to destination table. I ne...
Categories: DBA Blogs

Oracle Mobile Cloud Service (MCS): An introduction to API security: Basic Authentication and OAuth2

Amis Blog - Fri, 2017-04-07 07:41

As an integration/backend developer, when starting a project using Mobile Cloud Service, it is important to have some understanding of what this MBaaS (Mobile Backend as a Service) has to offer in terms of security features. This is important in order to be able to configure and test MCS. In this blog I will give examples on how to configure and use the basic authentication and OAuth2 features which are provided to secure APIs. You can read the Oracle documentation (which is quite good for MCS!) on this topic here.


Oracle Mobile Cloud Service offers platform APIs to offer specific features. You can create custom APIs by writing JavaScript code to run on Node.js. Connectors are used to access backend systems. This blogs focuses on authentication options for incoming requests.

The connectors are not directly available from the outside. MCS can secure custom and platform APIs. This functionality is taken care of by the Mobile Backend and the custom API configuration.

Getting started

The first thing to do when you want to expose an API is assign the API to a Mobile Backend. You can do this in the Mobile Backend configuration screen, APIs tab.

You can allow anonymous access, but generally you want to know who accesses your API. Also because MCS has a license option to pay for a specific number of API calls; you want to know who you are paying for. In order to require authentication on a per user basis, you first have to create a user and assign it to a group. You can also do this from the Mobile Backend configuration. Go to the Mobile Users Management tab to create users and groups.

After you have done this, you can assign the role to the API. You can also do this on a per endpoint basis which makes this authentication scheme very flexible.

Now we have configured our API to allow access to users who are in a specific role. We can now call our API using basic authentication or OAuth2.

Basic Authentication

In order to test our API, Postman is a suitable option. Postman is a freely available Chrome plugin (but also available standalone for several OSes) which provides many options for testing HTTP calls.

Basic authentication is a rather weak authentication mechanism. You Base64 encode a string username:password and send that as an HTTP header to the API you are calling. If someone intercepts the message, he/she can easily Base64 decode the username:password string to obtain the credentials. You can thus understand why I’ve blanked out that part of the Authorization field in several screenshots.

In addition to specifying the basic authentication header, you also need to specify the Oracle-Mobile-Backend-Id HTTP header which can be obtained from the main page of the Mobile Backend configuration page.

Obtain Oracle-Mobile-Backend-Id

Call your API with Basic authentication

This mechanism is rather straightforward. The authorization header needs to be supplied with every request though.


OAuth2 works a bit different than basic authentication in that first a token is obtained from a token service and the token is used in subsequent requests. When using the token, no additional authentication is required.

You can obtain the token from the Mobile Backend settings page as shown above. When you do a request to this endpoint, you need to provide some information:

You can use basic authentication with the Client ID:Client secret to access the token endpoint. These can be obtained from the screen shown below.

You also need to supply a username and password of the user for whom the token is generated. After you have done a request to the token service, you obtain a token.

This token can be used in subsequent request to your API. You can add the Bearer field with the token as Authentication HTTP header to authenticate instead of sending your username/password every time. This is thus more secure.


I’ve not talked about security options for outgoing requests provided by the supplied connectors.

These have per connector specific options and allow identity propagation. For example the REST connector (described in the Oracle documentation here) supports SAML tokens, CSF keys, basic authentication, OAuth2, JWT. The SOAP connector (see here) can use WS-Security in several flavours, SAML tokens, CSF keys, basic authentication, etc (quite a list).

The post Oracle Mobile Cloud Service (MCS): An introduction to API security: Basic Authentication and OAuth2 appeared first on AMIS Oracle and Java Blog.

Oracle Looking to Buy Accenture? Stranger Things Have Happened.

Abhinav Agarwal - Fri, 2017-04-07 07:30
Image credit: pixels.comThe Register reported that Oracle may be exploring the "feasibility of buying multi-billion dollar consultancy Accenture."

To summarize the numbers involved here, Oracle had FY16 revenues of $37 billion, net income of $8.9 billion, and a market cap of $180 billion.

On the other hand, Accenture had FY16 revenues of US$34.8 billion, net income of $4.1 billion, and a market cap of $77 billion.

Some questions that come to mind:
  1. Why? Oracle buying NetSuite in 2016 made sense. Oracle buying Salesforce would make even more sense. Oracle buying a management consulting and professional services company, and that too one with more than a quarter million employees, on the face of it, makes little sense. Would it help Oracle leapfrog Amazon's AWS cloud business? Would it help Oracle go after a new market segment? The answers are not clear, at all.
  2. Who would be in charge of this combined entity? Both have similar revenues, though Accenture has a market cap that is less than half Oracle's and a workforce that is roughly three times Oracle's. The cultural meshing itself would prove to be a challenge. Mark Hurd, one of two CEOs of Oracle (the other CEO is Safra Catz, a former investment banker), has the experience running a large, heterogeneous organization. Prior to his stint at Oracle, he was credited with making the HP and Compaq merger work. At Oracle, however, he has not run software product development, which has been run by Thomas Kurian, and who reports to Larry Ellison, and not Hurd. A merger between Oracle and Accenture would place an even greater emphasis on synergies between Oracle's software division and Accenture's consulting business.
  3. Oracle would need to spend close to $100 billion to buy Accenture, if it does. How would it finance it, even assuming it spends all its $68 billion in cash to do so? Keep in mind that its largest acquisition was in the range of $10 billion. The financial engineering would be staggering. It helps that it has a former investment banker as one of two CEOs.
  4. Will Oracle make Accenture focus on the Oracle red stack of software products and applications - both on-premise and in the cloud? If yes, it would need a much smaller-sized workforce than Accenture has. That in turn would diminish the value of Accenture to Oracle, and make the likely sticker price of $100 billion look even costlier.
  5. Is Oracle looking to become the IBM of the twenty-first century? It's certainly been a public ambition of Larry Ellison. In 2009, he said he wanted to pattern Oracle after Thomas Watson Jr's IBM, "combining both hardware and software systems." If Oracle keeps Accenture as a business unit free to pursue non-Oracle deals, does it mean Oracle is keen on morphing into a modern-day avatar of IBM and IBM Global Services, offering hardware, software, and professional services - all under one red, roof?
  6. Is Oracle serious about such a merger? An acquisition of this size seems more conjecture than in the realms of possibility, at least as of now. One is reminded of the time in 2003 when Microsoft explored the possibility of buying SAP. Those discussions went nowhere, and the idea was dropped. Combining two behemoths is no easy task, even for a company like Oracle, that has stitched together almost 50 acquisitions in just the last five years.
  7. If such an acquisition did go through, there would likely be few anti-trust concerns. That's a big "if".
  8. Stranger things have happened in the software industry, like HP buying Autonomy.
  9. I hope the Register piece was not an example of an early April Fool's joke.
(HT Sangram Aglave whose LinkedIn post alerted me to this article)

I first published this in LinkedIn Pulse on April 1, 2017.

© 2017, Abhinav Agarwal.

Oracle E-Business Suite 12.2 Web Services Security: Authentication and Authorization

This is the seventh posting in a blog series summarizing the new Oracle E-Business Suite 12.2 Mobile and web services functionality and recommendations for securing them.

Once traffic is accepted and passed by the URL Firewall, WebLogic initiates the standard Oracle E-Business Suite authentication and authorization procedures. Web services are authenticated and authorized no differently than for end-users.

Authorization rules for web services are relatively easy to configure in that all web services are defined as functions. The Oracle E-Business Suite's function security scheme and rules engine apply the same to GUI forms as for web services. In other words, the table APPLSYS.FND_FORM_FUNCTIONS defines all the forms that users use as well as defines all web services deployed. Menus then are built referencing these functions and Oracle E-Business Suite user accounts (APPLSYS.FND_USER) are given responsibilities with the menus of functions. These user accounts can be staff members or can be generic accounts (e.g. to support specific web services). Ensuring that appropriate users and responsibilities can call and use specific web services is the same critical step as ensuring that only appropriate users can use specific forms.

There are two authentication options for web services, local FND_USER passwords and tokens. Tokens can be SAML send vouchers/E-Business Suite Session Ids). Whichever is used, ensure that accounts are not inappropriately over privileged and the passwords and tokens not widely known and/or shared.

If you have any questions, please contact us at info@integrigy.com

-Michael Miller, CISSP-ISSMP, CCSP, CCSK

Web Services, DMZ/External, Oracle E-Business Suite
Categories: APPS Blogs, Security Blogs

Machine learning: Getting started with random forests in R

Amis Blog - Fri, 2017-04-07 02:08

According to Gartner, machine learning is on top of the hype cycle at the peak of inflated expectations. There is a lot of misunderstanding about what machine learning actually is and what it can be done with it.

Machine learning is not as abstract as one might think. If you want to get value out of known data and do predictions for unknown data, the most important challenge is asking the right questions and of course knowing what you are doing, especially if you want to optimize your prediction accuracy.

In this blog I’m exploring an example of machine learning. The random forest algorithm. I’ll provide an example on how you can use this algorithm to do predictions. In order to implement a random forest, I’m using R with the randomForest library and I’m using the iris data set which is provided by the R installation.

The Random Forest

A popular method of machine learning is by using decision tree learning. Decision tree learning comes closest to serving as an off-the-shelf procedure for data mining (see here). You do not need to know much about your data in order to be able to apply this method. The random forest algorithm is an example of a decision tree learning algorithm.

Random forest in (very) short

How it works exactly takes some time to figure out. If you want to know details, I recommend watching some youtube recordings of lectures on the topic. Some of its most important features of this method:

  • A random forest is a method to do classifications based on features. This implies you need to have features and classifications.
  • A random forest generates a set of classification trees (an ensemble) based on splitting a subset of features at locations which maximize information gain. This method is thus very suitable for distributed parallel computation.
  • Information gain can be determined by how accurate the splitting point is in determining the classification. Data is split based on the feature at a specific point and the classification on the left and right of the splitting point are checked. If for example the splitting point splits all data of a first classification from all data of a second classification, the confidence is 100%; maximum information gain.
  • A splitting point is a branching in the decision tree.
  • Splitting points are based on values of features (this is fast)
  • A random forest uses randomness to determine features to look at and randomness in the data used to construct the tree. Randomness helps reducing compute time.
  • Each tree gets to see a different dataset. This is called bagging.
  • Tree classification confidences are summed and averaged. Products of the confidences can also be taken. Individual trees have a high variance because they have only seen a small subset of data. Averaging helps creating a better result.
  • With correlated features, strong features can end up with low scores and the method can be biased towards variables with many categories.
  • A random forest does not perform well with unbalanced datasets; samples where there are more occurrences of a specific class.
Use case for a random forest

Use cases for a random forest can be for example text classification such as spam detection. Determine if certain words are present in a text can be used as a feature and the classification would be spam/not spam or even more specific such as news, personal, etc. Another interesting use case lies in genetics. Determining if the expression of certain genes is relevant for a specific disease. This way you can take someone’s DNA and determine with a certain confidence if someone will contract a disease. Of course you can also take other features into account such as income, education level, smoking, age, etc.

R Why R

I decided to start with R. Why? Mainly because it is easy. There are many libraries available and there is a lot of experience present worldwide; a lot of information can be found online. R however also has some drawbacks.

Some benefits

  • It is free and easy to get started. Hard to master though.
  • A lot of libraries are available. R package management works well.
  • R has a lot of users. There is a lot of information available online
  • R is powerful in that if you know what you are doing, you require little code doing it.

Some challenges

  • R loads datasets in memory
  • R is not the best at doing distributed computing but can do so. See for example here
  • The R syntax can be a challenge to learn
Getting the environment ready

I decided to install a Linux VM to play with. You can also install R and R studio (the R IDE) on Windows or Mac. I decided to start with Ubuntu Server. I first installed the usual things like a GUI. Next I installed some handy things like a terminal emulator, Firefox and stuff like that. I finished with installing R and R-studio.

So first download and install Ubuntu Server (next, next, finish)

sudo apt-get update
sudo apt-get install aptitude

–Install a GUI
sudo aptitude install –without-recommends ubuntu-desktop

— Install the VirtualBox Guest additions
sudo apt-get install build-essential linux-headers-$(uname -r)
Install guest additions (first mount the ISO image which is part of VirtualBox, next run the installer)

— Install the below stuff to make Dash (Unity search) working
sudo apt-get install unity-lens-applications unity-lens-files

— A shutdown button might come in handy
sudo apt-get install indicator-session

— Might come in handy. Browser and fancy terminal application
sudo apt-get install firefox terminator

–For the installation of R I used the following as inspiration: https://www.r-bloggers.com/how-to-install-r-on-linux-ubuntu-16-04-xenial-xerus/
sudo echo “deb http://cran.rstudio.com/bin/linux/ubuntu xenial/” | sudo tee -a /etc/apt/sources.list
gpg –keyserver keyserver.ubuntu.com –recv-key E084DAB9
gpg -a –export E084DAB9 | sudo apt-key add –
sudo apt-get update
sudo apt-get install r-base r-base-dev

— For the installation of R-studio I used: https://mikewilliamson.wordpress.com/2016/11/14/installing-r-studio-on-ubuntu-16-10/

wget http://ftp.ca.debian.org/debian/pool/main/g/gstreamer0.10/libgstreamer0.10-0_0.10.36-1.5_amd64.deb
wget http://ftp.ca.debian.org/debian/pool/main/g/gst-plugins-base0.10/libgstreamer-plugins-base0.10-0_0.10.36-2_amd64.deb
sudo dpkg -i libgstreamer0.10-0_0.10.36-1.5_amd64.deb
sudo dpkg -i libgstreamer-plugins-base0.10-0_0.10.36-2_amd64.deb
sudo apt-mark hold libgstreamer-plugins-base0.10-0
sudo apt-mark hold libgstreamer0.10

wget https://download1.rstudio.org/rstudio-1.0.136-amd64.deb
sudo dpkg -i rstudio-1.0.136-amd64.deb
sudo apt-get -f install

Doing a random forest in R

R needs some libraries to do random forests and create nice plots. First give the following commands:

#to do random forests

#to work with R markdown language

#to create nice plots

In order to get help on a library you can give the following command which will give you more information on the library.

library(help = “randomForest”)

 Of course, the randomForest implementation does have some specifics:

  • it uses the reference implementation based on CART trees
  • it is biased in favor of continuous variables and variables with many categories

A simple program to do a random forest looks like this:

#load libraries

#random numbers after the set.seed(10) are reproducible if I do set.seed(10) again

#create a training sample of 45 items from the iris dataset. replace indicates items can only be present once in the dataset. If replace is set to true, you will get Out of bag errors.
idx_train <- sample(1:nrow(iris), 45, replace = FALSE)

#create a data.frame from the data which is not in the training sample
tf_test <- !1:nrow(iris) %in% idx_train

#the column ncol(iris) is the last column of the iris dataset. this is not a feature column but a classification column
feature_columns <- 1:(ncol(iris)-1)

#generate a randomForest.
#use the feature columns from training set for this
#iris[idx_train, ncol(iris)] indicates the classification column
#importance=TRUE indicates the importance of features in determining the classification should be determined
#y = iris[idx_train, ncol(iris)] gives the classifications for the provided data
#ntree=1000 indicates 1000 random trees will be generated
model <- randomForest(iris[idx_train, feature_columns], y = iris[idx_train, ncol(iris)], importance = TRUE, ntree = 1000)

#print the model
#printing the model indicates how the sample dataset is distributed among classes. The sum of the sample classifications is 45 which is the sample size. OOB rate indicates ‘out of bag’ (the overall classification error).


#we use the model to predict the class based on the feature columns of the dataset (minus the sample used to train the model).
response <- predict(model, iris[tf_test, feature_columns])

#determine the number of correct classifications
correct <- response == iris[tf_test, ncol(iris)]

#determine the percentage of correct classifications
sum(correct) / length(correct)

#print a variable importance (varImp) plot of the randomForest

#in this dataset the petal length and width are more important measures to determine the class than the sepal length and width.

The post Machine learning: Getting started with random forests in R appeared first on AMIS Oracle and Java Blog.

Oracle Code : See you there!

Tim Hall - Fri, 2017-04-07 01:30

You may have seen a lot of tweets (#OracleCode) recently about the Oracle Code events around the world.

The content of the events is rather different to the typical Oracle events I go to, so it will be a good opportunity for me to learn some new stuff.

I’ll be speaking at two of the European events this year.

They are Oracle events, so there is bound to be an Oracle spin on things, but I think it’s a welcome change of tack for Oracle to acknowledge that they are not always the centre of the universe in the minds of developers. If there is an event near you, check it out and see what is happening in the development world these days.



Oracle Code : See you there! was first posted on April 7, 2017 at 7:30 am.
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Workaround for ADF BC View Object Attribute Order Problem in JDeveloper 12c

Andrejus Baranovski - Thu, 2017-04-06 21:23
I'm sure probably every ADF developer sooner or later faced this issue. When you create VO based on EO, JDEV gives you alphabetically ordered list of attributes. As a result - order of attributes in EO and VO becomes different. While this doesn't influence runtime functionality, it becomes quite annoying for application maintenance. Hard to match attributes between VO and EO, developer need to search through the list to locate attribute he is looking for. But there is a workaround, I will describe it here.

Let's see what the problem first. Assume we have Employees EO, attributes are generated in the same order as DB table columns:

Now if you are using VO creation wizard, list of attributes will be displayed in alphabetic order. This is frustrating:

Without any other choice, developer would select EO attributes and select them in such order as it is listed:

But wait, there is a workaround. Don't select all attributes, instead select only EO item itself. Then use Add button to add entire list of EO attributes:

This time attributes will be added in original order, as the order is set in EO.

Enjoy this small, but useful hint.


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