Oracle launches its version of R #rstats

From-

http://www.oracle.com/us/corporate/press/1515738

Integrates R Statistical Programming Language into Oracle Database 11g

News Facts

Oracle today announced the availability of Oracle Advanced Analytics, a new option for Oracle Database 11g that bundles Oracle R Enterprise together with Oracle Data Mining.
Oracle R Enterprise delivers enterprise class performance for users of the R statistical programming language, increasing the scale of data that can be analyzed by orders of magnitude using Oracle Database 11g.
R has attracted over two million users since its introduction in 1995, and Oracle R Enterprise dramatically advances capability for R users. Their existing R development skills, tools, and scripts can now also run transparently, and scale against data stored in Oracle Database 11g.
Customer testing of Oracle R Enterprise for Big Data analytics on Oracle Exadata has shown up to 100x increase in performance in comparison to their current environment.
Oracle Data Mining, now part of Oracle Advanced Analytics, helps enable customers to easily build and deploy predictive analytic applications that help deliver new insights into business performance.
Oracle Advanced Analytics, in conjunction with Oracle Big Data ApplianceOracle Exadata Database Machine and Oracle Exalytics In-Memory Machine, delivers the industry’s most integrated and comprehensive platform for Big Data analytics.

Comprehensive In-Database Platform for Advanced Analytics

Oracle Advanced Analytics brings analytic algorithms to data stored in Oracle Database 11g and Oracle Exadata as opposed to the traditional approach of extracting data to laptops or specialized servers.
With Oracle Advanced Analytics, customers have a comprehensive platform for real-time analytic applications that deliver insight into key business subjects such as churn prediction, product recommendations, and fraud alerting.
By providing direct and controlled access to data stored in Oracle Database 11g, customers can accelerate data analyst productivity while maintaining data security throughout the enterprise.
Powered by decades of Oracle Database innovation, Oracle R Enterprise helps enable analysts to run a variety of sophisticated numerical techniques on billion row data sets in a matter of seconds making iterative, speed of thought, and high-quality numerical analysis on Big Data practical.
Oracle R Enterprise drastically reduces the time to deploy models by eliminating the need to translate the models to other languages before they can be deployed in production.
Oracle R Enterprise integrates the extensive set of Oracle Database data mining algorithms, analytics, and access to Oracle OLAP cubes into the R language for transparent use by R users.
Oracle Data Mining provides an extensive set of in-database data mining algorithms that solve a wide range of business problems. These predictive models can be deployed in Oracle Database 11g and use Oracle Exadata Smart Scan to rapidly score huge volumes of data.
The tight integration between R, Oracle Database 11g, and Hadoop enables R users to write one R script that can run in three different environments: a laptop running open source R, Hadoop running with Oracle Big Data Connectors, and Oracle Database 11g.
Oracle provides single vendor support for the entire Big Data platform spanning the hardware stack, operating system, open source R, Oracle R Enterprise and Oracle Database 11g.
To enable easy enterprise-wide Big Data analysis, results from Oracle Advanced Analytics can be viewed from Oracle Business Intelligence Foundation Suite and Oracle Exalytics In-Memory Machine.

Supporting Quotes

“Oracle is committed to meeting the challenges of Big Data analytics. By building upon the analytical depth of Oracle SQL, Oracle Data Mining and the R environment, Oracle is delivering a scalable and secure Big Data platform to help our customers solve the toughest analytics problems,” said Andrew Mendelsohn, senior vice president, Oracle Server Technologies.
“We work with leading edge customers who rely on us to deliver better BI from their Oracle Databases. The new Oracle R Enterprise functionality allows us to perform deep analytics on Big Data stored in Oracle Databases. By leveraging R and its library of open source contributed CRAN packages combined with the power and scalability of Oracle Database 11g, we can now do that,” said Mark Rittman, co-founder, Rittman Mead.
Oracle Advanced Analytics — an option to Oracle Database 11g Enterprise Edition – extends the database into a comprehensive advanced analytics platform through two major components: Oracle R Enterprise and Oracle Data Mining. With Oracle Advanced Analytics, customers have a comprehensive platform for real-time analytic applications that deliver insight into key business subjects such as churn prediction, product recommendations, and fraud alerting.

Oracle R Enterprise tightly integrates the open source R programming language with the database to further extend the database with Rs library of statistical functionality, and pushes down computations to the database. Oracle R Enterprise dramatically advances the capability for R users, and allows them to use their existing R development skills and tools, and scripts can now also run transparently and scale against data stored in Oracle Database 11g.

Oracle Data Mining provides powerful data mining algorithms that run as native SQL functions for in-database model building and model deployment. It can be accessed through the SQL Developer extension Oracle Data Miner to build, evaluate, share and deploy predictive analytics methodologies. At the same time the high-performance Oracle-specific data mining algorithms are accessible from R.

BENEFITS

  • Scalability—Allows customers to easily scale analytics as data volume increases by bringing the algorithms to where the data resides – in the database
  • Performance—With analytical operations performed in the database, R users can take advantage of the extreme performance of Oracle Exadata
  • Security—Provides data analysts with direct but controlled access to data in Oracle Database 11g, accelerating data analyst productivity while maintaining data security
  • Save Time and Money—Lowers overall TCO for data analysis by eliminating data movement and shortening the time it takes to transform “raw data” into “actionable information”
Oracle R Hadoop Connector Gives R users high performance native access to Hadoop Distributed File System (HDFS) and MapReduce programming framework.
This is a  R package
From the datasheet at

Exciting Contest at CrowdANALYTIX

A new contest from a relatively new website. This one is fast and furious and has a decent chunk of money!

 

From

 

http://www.crowdanalytix.com/contests/airport-guest-sentiment-analysis-1544282253/view/

 

Submission Deadline:
Sun, 26 February 2012 05:00 AM UTC
Results Announced by:
Mon, 05 March 2012 05:00 AM UTC
Category: Text Analytics Function: Aerospace & Aviation

 

Title
Analysis of sentiment and its intensity – feedback from airport guests
Description
ABC (name intentionally obfuscated) is one of the best managed and highly profitable airports  in India. As with all well managed airports, ABC would like to understand what guests feel about their experience when traveling, using or transiting through their airport. ABC has a website in which guests can visit and leave behind a comment, agree or disagree with others’ comments, or respond to a comment confirming or negating the expressed opinion.

The goal of this contest is to create a summarization of the opinions, feelings and sentiments expressed in the comments left behind by guests on the website. This information is being provided as data for solvers. Some understanding of the intensity of the opinion, feeling or sentiment will also be useful. For example, if there is a consistent demand for more spas across guest conversations, it needs to be highlighted.  Consistent positive or negative sentiments and opinions need to be discovered and highlighted.
Data
Guest comments have been crawled and provided to you. The data consists approximately 1000 comments from guests including the timestamp of those comments.  Personal information (name, email etc) have been hidden. This data is publicly available
Solver Expectations:
Participants may submit entries before the deadline. If a participant submits multiple entries, the entry submitted last before the deadline will be considered as the participant’s submission.
The following deliverables are expected to be submitted:
  • a report expressing the results of the opinion and sentiment mining
  • documentation about how you approached the problem, what tools, technologies and languages you used, and what problems you encountered
Timeline and Prizes: 
This contest begin on 16 Feb 2012 and will last for a duration of 9 days.
Prizes:
  • One 1st Prize – $1000
  • One 2nd Prize – $500
  • Two 3rd Prizes – $250

New Plotters in Rapid Miner 5.2

I almost missed this because of my vacation and traveling

Rapid Miner has a tonne of new stuff (Statuary Ethics Declaration- Rapid Miner has been an advertising partner for Decisionstats – see the right margin)

see

http://rapid-i.com/component/option,com_myblog/Itemid,172/lang,en/

Great New Graphical Plotters

and some flashy work

and a great series of educational lectures

A Simple Explanation of Decision Tree Modeling based on Entropies

Link: http://www.simafore.com/blog/bid/94454/A-simple-explanation-of-how-entropy-fuels-a-decision-tree-model

Description of some of the basics of decision trees. Simple and hardly any math, I like the plots explaining the basic idea of the entropy as splitting criterion (although we actually calculate gain ratio differently than explained…)

Logistic Regression for Business Analytics using RapidMiner

Link: http://www.simafore.com/blog/bid/57924/Logistic-regression-for-business-analytics-using-RapidMiner-Part-2

Same as above, but this time for modeling with logistic regression.
Easy to read and covering all basic ideas together with some examples. If you are not familiar with the topic yet, part 1 (see below) might help.

Part 1 (Basics): http://www.simafore.com/blog/bid/57801/Logistic-regression-for-business-analytics-using-RapidMiner-Part-1

Deploy Model: http://www.simafore.com/blog/bid/82024/How-to-deploy-a-logistic-regression-model-using-RapidMiner

Advanced Information: http://www.simafore.com/blog/bid/99443/Understand-3-critical-steps-in-developing-logistic-regression-models

and lastly a new research project for collaborative data mining

http://www.e-lico.eu/

e-LICO Architecture and Components

The goal of the e-LICO project is to build a virtual laboratory for interdisciplinary collaborative research in data mining and data-intensive sciences. The proposed e-lab will comprise three layers: the e-science and data mining layers will form a generic research environment that can be adapted to different scientific domains by customizing the application layer.

  1. Drag a data set into one of the slots. It will be automatically detected as training data, test data or apply data, depending on whether it has a label or not.
  2. Select a goal. The most frequent one is probably “Predictive Modelling”. All goals have comments, so you see what they can be used for.
  3. Select “Fetch plans” and wait a bit to get a list of processes that solve your problem. Once the planning completes, select one of the processes (you can see a preview at the right) and run it. Alternatively, select multiple (selecting none means selecting all) and evaluate them on your data in a batch.

The assistant strives to generate processes that are compatible with your data. To do so, it performs a lot of clever operations, e.g., it automatically replaces missing values if missing values exist and this is required by the learning algorithm or performs a normalization when using a distance-based learner.

You can install the extension directly by using the Rapid-I Marketplace instead of the old update server. Just go to the preferences and enter http://rapidupdate.de:8180/UpdateServer as the update URL

Of course Rapid Miner has been of the most professional open source analytics company and they have been doing it for a long time now. I am particularly impressed by the product map (see below) and the graphical user interface.

http://rapid-i.com/content/view/186/191/lang,en/

Product Map

Just click on the products in the overview below in order to get more information about Rapid-I products.

 

Rapid-I Product Overview 

 

Radoop 0.3 launched- Open Source Graphical Analytics meets Big Data

What is Radoop? Quite possibly an exciting mix of analytics and big data computing

 

http://blog.radoop.eu/?p=12

What is Radoop?

Hadoop is an excellent tool for analyzing large data sets, but it lacks an easy-to-use graphical interface. RapidMiner is an excellent tool for data analytics, but its data size is limited by the memory available, and a single machine is often not enough to run the analyses on time. In this project, we combine the strengths of both projects and provide a RapidMiner extension for editing and running ETL, data analytics and machine learning processes over Hadoop.

We have closely integrated the highly optimized data analytics capabilities of Hive and Mahout, and the user-friendly interface of RapidMiner to form a powerful and easy-to-use data analytics solution for Hadoop.

 

and what’s new

http://blog.radoop.eu/?p=198

Radoop 0.3 released – fully graphical big data analytics

Today, Radoop had a major step forward with its 0.3 release. The new version of the visual big data analytics package adds full support for all major Hadoop distributions used these days: Apache Hadoop 0.20.2, 0.20.203, 1.0 and Cloudera’s Distribution including Apache Hadoop 3 (CDH3). It also adds support for large clusters by allowing the namenode, the jobtracker and the Hive server to reside on different nodes.

As Radoop’s promise is to make big data analytics easier, the 0.3 release is also focused on improving the user interface. It has an enhanced breakpointing system which allows to investigate intermediate results, and it adds dozens of quick fixes, so common process design mistakes get much easier to solve.

There are many further improvements and fixes, so please consult the release notes for more details. Radoop is in private beta mode, but heading towards a public release in Q2 2012. If you would like to get early access, then please apply at the signup page or describe your use case in email (beta at radoop.eu).

Radoop 0.3 (15 February 2012)

  • Support for Apache Hadoop 0.20.2, 0.20.203, 1.0 and Cloudera’s Distribution Including Apache Hadoop 3 (CDH3) in a single release
  • Support for clusters with separate master nodes (namenode, jobtracker, Hive server)
  • Enhanced breakpointing to evaluate intermediate results
  • Dozens of quick fixes for the most common process design errors
  • Improved process design and error reporting
  • New welcome perspective to help in the first steps
  • Many bugfixes and performance improvements

Radoop 0.2.2 (6 December 2011)

  • More Aggregate functions and distinct option
  • Generate ID operator for convenience
  • Numerous bug fixes and improvements
  • Improved user interface

Radoop 0.2.1 (16 September 2011)

  • Set Role and Data Multiplier operators
  • Management panel for testing Hadoop connections
  • Stability improvements for Hive access
  • Further small bugfixes and improvements

Radoop 0.2 (26 July 2011)

  • Three new algoritms: Fuzzy K-Means, Canopy, and Dirichlet clustering
  • Three new data preprocessing operators: Normalize, Replace, and Replace Missing Values
  • Significant speed improvements in data transmission and interactive analytics
  • Increased stability and speedup for K-Means
  • More flexible settings for Join operations
  • More meaningful error messages
  • Other small bugfixes and improvements

Radoop 0.1 (14 June 2011)

Initial release with 26 operators for data transmission, data preprocessing, and one clustering algorithm.

Note that Rapid Miner also has a great R extension so you can use R, a graphical interface and big data analytics is now easier and more powerful than ever.


Machine Learning for Hackers – #rstats

I got the incredible and intriguing Machine Learning for Hackers for just $15.99 for an electronic copy from O Reilly Media. (Deal of the Day!)

It has just been launched this month!!

It is an incredible book- and I really  like the way O Reilly has made it so easy to download E Books

I am trying to read it while trying to a write a whole lot of other stuff— and it seems easy to read and understand even for non-hackers like me. Esp with Stanford delaying its online machine learning course- this is one handy e-book to have  to get you started in ML and data science!!

Click the image to see the real deal.

http://shop.oreilly.com/product/0636920018483.do

 

How to find out people who are spamming you

Step 1-

We assume you have Gmail. If you dont have Gmail, you deserve the Spam

You click -show original on the drop down in the spammy message

 

you see a lot of mumbo jumbo

(or you just pick the IP addresses from comment spam)

Step 2-

You pick the IP addresses from the mumbo jumbo above (called headers )

http://en.wikipedia.org/wiki/IP_address

An Internet Protocol address (IP address) is a numerical label assigned to each device (e.g., computer, printer) participating in a computer networkthat uses the Internet Protocol for communication.[1] An IP address serves two principal functions: host or network interface identification and locationaddressing

Step 3-

You find out who has that IP address using arin

https://www.arin.net/

 

Step 4-

You put those IP addresses in your firewall for your computer

http://technet.microsoft.com/en-us/library/cc733090(v=ws.10).aspx

(or if you have a self-hosted blog using Website cpanel ip deny)

http://www.siteground.com/tutorials/cpanel/ip_deny_manager.htm

Step 5-

 

Communicate to that IP Address using IRC

http://en.wikipedia.org/wiki/Internet_Relay_Chat

Internet Relay Chat (IRC) is a protocol for real-time Internet text messaging (chat) or synchronous conferencing.[1] It is mainly designed for group communication in discussion forums, called channels,[2] but also allows one-to-one communication via private message[3] as well as chat and data transfer,[4] including file sharing.[5]

or use HOIC to test your own firewall better before people  spam  you

http://gizmodo.com/5883146/what-is-hoic or

http://www.decisionstats.com/occupy-the-internet/

 

Internet Encryption Algols are flawed- too little too late!

Some news from a paper I am reading- not surprised that RSA has a problem .

http://eprint.iacr.org/2012/064.pdf

Abstract. We performed a sanity check of public keys collected on the web. Our main goal was to test the validity of the assumption that di erent random choices are made each time keys are generated.We found that the vast majority of public keys work as intended. A more disconcerting fi nding is that two out of every one thousand RSA moduli that we collected off er no security.

 

Our conclusion is that the validity of the assumption is questionable and that generating keys in the real world for multiple-secrets” cryptosystems such as RSA is signi cantly riskier than for single-secret” ones such as ElGamal or (EC)DSA which are based on Die-Hellman.

Keywords: Sanity check, RSA, 99.8% security, ElGamal, DSA, ECDSA, (batch) factoring, discrete logarithm, Euclidean algorithm, seeding random number generators, K9.

and

 

99.8% Security. More seriously, we stumbled upon 12720 di erent 1024-bit RSA moduli that o ffer no security. Their secret keys are accessible to anyone who takes the trouble to redo our work. Assuming access to the public key collection, this is straightforward compared to more

traditional ways to retrieve RSA secret keys (cf. [5,15]). Information on the a ected X.509 certi cates and PGP keys is given in the full version of this paper, cf. below. Overall, over the data we collected 1024-bit RSA provides 99.8% security at best (but see Appendix A).

 

However no algol is perfect and even Elliptic Based Crypto ( see http://en.wikipedia.org/wiki/Elliptic_curve_cryptography#Fast_reduction_.28NIST_curves.29 )has a flaw called Shor http://en.wikipedia.org/wiki/Shor%27s_algorithm

Funny thing is ECC is now used for Open DNS


http://dnscurve.org/crypto.html

The DNSCurve project adds link-level public-key protection to DNS packets. This page discusses the cryptographic tools used in DNSCurve.

ELLIPTIC-CURVE CRYPTOGRAPHY

DNSCurve uses elliptic-curve cryptography, not RSA.

RSA is somewhat older than elliptic-curve cryptography: RSA was introduced in 1977, while elliptic-curve cryptography was introduced in 1985. However, RSA has shown many more weaknesses than elliptic-curve cryptography. RSA’s effective security level was dramatically reduced by the linear sieve in the late 1970s, by the quadratic sieve and ECM in the 1980s, and by the number-field sieve in the 1990s. For comparison, a few attacks have been developed against some rare elliptic curves having special algebraic structures, and the amount of computer power available to attackers has predictably increased, but typical elliptic curves require just as much computer power to break today as they required twenty years ago.

IEEE P1363 standardized elliptic-curve cryptography in the late 1990s, including a stringent list of security criteria for elliptic curves. NIST used the IEEE P1363 criteria to select fifteen specific elliptic curves at five different security levels. In 2005, NSA issued a new “Suite B” standard, recommending the NIST elliptic curves (at two specific security levels) for all public-key cryptography and withdrawing previous recommendations of RSA.

Some specific types of elliptic-curve cryptography are patented, but DNSCurve does not use any of those types of elliptic-curve cryptography.

No wonder college kids are hacking defense databases easily nowadays!!