Search results “Data mining sas pdf wrap”
SAS Visual Data Mining and Machine Learning
http://www.sas.com/vdmml Boost analytical productivity and solve your most complex problems faster with a single, integrated in-memory environment that's both open and scalable. SAS VISUAL DATA MINING AND MACHINE LEARNING SAS Visual Data Mining and Machine Learning supports the end-to-end data mining and machine-learning process with a comprehensive, visual (and programming) interface that handles all tasks in the analytical life cycle. It suits a variety of users and there is no application switching. From data management to model development and deployment, everyone works in the same, integrated environment. http://www.sas.com/vdmml SUBSCRIBE TO THE SAS SOFTWARE YOUTUBE CHANNEL http://www.youtube.com/subscription_center?add_user=sassoftware ABOUT SAS SAS is the leader in analytics. Through innovative analytics, business intelligence and data management software and services, SAS helps customers at more than 75,000 sites make better decisions faster. Since 1976, SAS has been giving customers around the world THE POWER TO KNOW®. VISIT SAS http://www.sas.com CONNECT WITH SAS SAS ► http://www.sas.com SAS Customer Support ► http://support.sas.com SAS Communities ► http://communities.sas.com Facebook ► https://www.facebook.com/SASsoftware Twitter ► https://www.twitter.com/SASsoftware LinkedIn ► http://www.linkedin.com/company/sas Google+ ► https://plus.google.com/+sassoftware Blogs ► http://blogs.sas.com RSS ►http://www.sas.com/rss
Views: 5174 SAS Software
Importing Data into R - How to import csv and text files into R
In this video you will learn how to import your flat files into R. Want to take the interactive coding exercises and earn a certificate? Join DataCamp today, and start our intermediate R tutorial for free: https://www.datacamp.com/courses/importing-data-into-r In this first chapter, we'll start with flat files. They're typically simple text files that contain table data. Have a look at states.csv, a flat file containing comma-separated values. The data lists basic information on some US states. The first line here gives the names of the different columns or fields. After that, each line is a record, and the fields are separated by a comma, hence the name comma-separated values. For example, there's the state Hawaii with the capital Honolulu and a total population of 1.42 million. What would that data look like in R? Well, actually, the structure nicely corresponds to a data frame in R, that ideally looks like this: the rows in the data frame correspond to the records and the columns of the data frame correspond to the fields. The field names are used to name the data frame columns. But how to go from the CSV file to this data frame? The mother of all these data import functions is the read.table() function. It can read in any file in table format and create a data frame from it. The number of arguments you can specify for this function is huge, so I won't go through each and every one of these arguments. Instead, let's have a look at the read.table() call that imports states.csv and try to understand what happens. The first argument of the read.table() function is the path to the file you want to import into R. If the file is in your current working directory, simply passing the filename as a character string works. If your file is located somewhere else, things get tricky. Depending on the platform you're working on, Linux, Microsoft, Mac, whatever, file paths are specified differently. To build a path to a file in a platform-independent way, you can use the file.path() function. Now for the header argument. If you set this to TRUE, you tell R that the first row of the text file contains the variable names, which is the case here. read.table() sets this argument FALSE by default, which would mean that the first row is already an observation. Next, sep is the argument that specifies how fields in a record are separated. For our csv file here, the field separator is a comma, so we use a comma inside quotes. Finally, the stringsAsFactors argument is pretty important. It's TRUE by default, which means that columns, or variables, that are strings, are imported into R as factors, the data structure to store categorical variables. In this case, the column containing the country names shouldn't be a factor, so we set stringsAsFactors to FALSE. If we actually run this call now, we indeed get a data frame with 5 observations and 4 variables, that corresponds nicely to the CSV file we started with. The read table function works fine, but it's pretty tiring to specify all these arguments every time, right? CSV files are a common and standardized type of flat files. That's why the utils package also provides the read.csv function. This function is a wrapper around the read.table() function, so read.csv() calls read.table() behind the scenes, but with different default arguments to match with the CSV format. More specifically, the default for header is TRUE and for sep is a comma, so you don't have to manually specify these anymore. This means that this read.table() call from before is thus exactly the same as this read.csv() call. Apart from CSV files, there are also other types of flat files. Take this tab-delimited file, states.txt, with the same data: To import it with read.table(), you again have to specify a bunch of arguments. This time, you should point to the .txt file instead of the .csv file, and the sep argument should be set to a tab, so backslash t. You can also use the read.delim() function, which again is a wrapper around read.table; the default arguments for header and sep are adapted, among some others. The result of both calls is again a nice translation of the flat file to a an R data frame. Now, there's one last thing I want to discuss here. Have a look at this US csv file and its european counterpart, states_eu.csv. You'll notice that the Europeans use commas for decimal points, while normally one uses the dot. This means that they can't use the comma as the field-delimiter anymore, they need a semicolon. To deal with this easily, R provides the read.csv2() function. Both the sep argument as the dec argument, to tell which character is used for decimal points, are different. Likewise, for read.delim() you have a read.delim2() alternative. Can you spot the differences again? This time, only the dec argument had to change.
Views: 50392 DataCamp
Boomerang Trick Shots | Dude Perfect
Time to take boomerangs to the next level! ► Click HERE to subscribe to Dude Perfect! http://bit.ly/SubDudePerfect ► Click HERE to watch our most recent videos! http://bit.ly/NewestDudePerfectVideos http://bit.ly/NewestDPVideos ►Click HERE to follow Logan on Instagram! Follow @logan.broadbent: https://www.instagram.com/logan.broadbent ► SHOP our NEW Merchandise! - http://bit.ly/DPStore ►Click HERE to join the exclusive Dude Perfect T-Shirt Club! http://bit.ly/DPTShirtClub Music: Army by Zayde Wolf ►Click HERE to download : http://smarturl.it/ZWGoldenAge Play our NEW iPhone game! ► PLAY Endless Ducker on iPhone -- http://smarturl.it/EndlessDucker ► PLAY Endless Ducker on Android -- http://smarturl.it/EndlessDucker ► VISIT our NEW STORE - http://bit.ly/DPStore ► JOIN our NEWSLETTER - http://bit.ly/DPNewsletterEndCard ► WATCH our STEREOTYPES - http://bit.ly/StereotypesPlaylist In between videos we hang out with you guys on Instagram, Snapchat, Twitter, and Facebook so pick your favorite one and hang with us there too! http://Instagram.com/DudePerfect http://bit.ly/DudePerfectSnapchat http://Twitter.com/DudePerfect http://Facebook.com/DudePerfect Do you have a GO BIG mindset? See for yourself in our book "Go Big." ►http://amzn.to/OYdZ2s A special thanks to those of you who play our iPhone Games and read our book. You guys are amazing and all the great things you tell us about the game and the book make those projects so worthwhile for us! Dude Perfect GAME - http://smarturl.it/DPGameiPhone Dude Perfect BOOK - "Go Big" - http://amzn.to/OYdZ2s Click here if you want to learn more about Dude Perfect: http://www.dudeperfect.com/blog-2/ Bonus points if you're still reading this! Comment As always...Go Big and God Bless! - Your friends at Dude Perfect Business or Media, please contact us at: [email protected] ------------ 5 Best Friends and a Panda. If you like Sports + Comedy, come join the Dude Perfect team! Best known for trick shots, stereotypes, battles, bottle flips, ping pong shots and all around competitive fun, Dude Perfect prides ourselves in making the absolute best family-friendly entertainment possible! Welcome to the crew! Pound it. Noggin. - Dude Perfect
Views: 53562923 Dude Perfect
Frequency Polygons - Data Analysis with R
This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 9245 Udacity
Mining the FDA Adverse Event Reporting System with Oracle Empirica Signal
Learn how to identify safety and pharmacovigilance signals by data mining FAERS with Oracle's Empirica Signal. -- Ever since the European Union (EU) introduced new legislation that requires life sciences companies to proactively detect, prioritize, and evaluate safety signals, there has been an increased interest, not only from sponsors and CROs in the EU, but globally, in pharmacovigilance systems that can assist with the signal management process. Please join Perficient's Chris Wocosky, an expert in signal detection and management, for this video in which she discussed how your organization can use Empirica Signal, Oracle's state-of-the-art signal detection system to data mine the existing FDA Adverse Event Reporting System (FAERS) to determine safety signals. This video will help you to better understand how this solution can be used in daily pharmacovigilance activities. To view this webinar in its entirety, please visit: https://cc.readytalk.com/r/7ekwxbm7q33t&eom Stay on top of Life Sciences technologies by following us here: Twitter: http://www.twitter.com/Perficient_LS Facebook: http://www.facebook.com/Perficient LinkedIn: http://www.linkedin.com/company/165444 Google+: https://plus.google.com/+Perficient SlideShare: http://www.slideshare.net/PerficientInc
Views: 4852 Perficient, Inc.
Visual Basic Programming lesson 12 - Reading data from a text file
A lesson requested by a subscriber. This lesson teaches you how to read data from a text file. In the next few lessons we are also going to talk about how to store data in a text file, which will help you with projects such as develop a high score table in game creation. Visit http://www.magicmonktutorials.com to download source code.
Views: 73855 Magic Monk
101 Great Answers To The Toughest Interview Questions ©
This is an excellent guide to attend interviews. 101 Great Answers To The Toughest Interview Questions contains a collection of all possible interview questions and how to answer and face them in a typical interview. A prospective job seeker can also get excellent tips to cracking hard interview questions in this video. Learn to crack your interview today! The interviewing process is a kind of sale. In this case, you are the product—and the salesperson. If you show up unprepared to talk about your unique features and benefits, you're not likely to motivate an interviewer to "buy." The sad fact is that many job candidates are unprepared to talk about themselves. You may have mailed a gorgeous resume and cover letter. You may be wearing the perfect clothes on the day of the interview. But if you can't convince the interviewer—face to face—that you are the right person for the job, you aren't likely to make the sale. Too many candidates hesitate after the first open-ended question, then stumble and stutter their way through a disjointed litany of resume "sound bites." Other interviewees recite canned replies that only highlight their memory skills. The days of filling out the standard application and chatting your way through one or two interviews are gone. These days, interviewers and hiring managers are reluctant to leave anything to chance. Many have begun to experiment with the latest techniques for data-gathering and analysis. For employers, interviewing has become a full-fledged science. More employers seem to be looking for a special kind of employee—someone with experience, confidence, and the initiative to learn what he or she needs to know. Someone who requires very little supervision. Someone with a hands-on attitude—from beginning to end. Because employers can't tell all that from a job application and a handshake, here's what they're making you do: Pass the test(s). You'll probably have to go through more interviews than your predecessors for the same job—no matter what your level of expertise. Knowledge and experience still give you an inside edge. But these days, you'll need stamina, too. Your honesty, your intelligence, your mental health—even the toxicity of your blood—may be measured before you can be considered fully assessed. Brave more interviews. You may also have to tiptoe through a mine field of different types of interview situations—and keep your head—to survive as a new hire. Don't go out and subscribe to a human resources journal. Just do all you can to remain confident and flexible—and ready with your answers. No matter what kind of interview you find yourself in, this approach should carry you through with flying colors. Let's take a brief, no-consequences tour of the interview circuit. What (Who) are You Up Against? There are three predominant interviewing types or styles: the Telephone Screener, the Human Screen, and the Manager. Which is which, and why would someone be considered one or the other? While personal temperament is one factor, the adoption of one or the other style is primarily a function of the interviewer's role in the organization and his or her daily workload. The Human Screen Many human resource and personnel professionals fall into this category. For these people, interviewing is not simply just a once-a-quarter or once-a-month event, but rather a key part of their daily job description. They meet and interview many people, and are more likely than either of the other two categories to consider an exceptional applicant for more than one possible opening within the organization. A primary objective of the Human Screen is to develop a strong group of candidates for Managers (see category three) to interview in person. To do this, of course, they must fend off many applicants and callers—a daunting task, because the Human Screen or the department in which he or she works is often the only contact provided in employment advertisements. Among the most common reasons for removal from the Human Screen's "hot" list are: lack of formal or informal qualifications as outlined in the organization's job description; sudden changes in hiring priorities and personnel requirements; poor performance during the in-person interview itself; and inaction due to the Human Screen's uncertainty about your current status or contact information. That last reason is more common than you might imagine. Human Screens are constantly swamped with phone calls, resumes, and unannounced visits from hopeful applicants. Odds are that despite their best efforts, they sometimes lose track of qualified people. Subscribe to our Channel at http://www.youtube.com/theinterviewskills Follow us on our Official Facebook Fanpage at http://www.facebook.com/theinterviewskills Link to this video http://www.youtube.com/watch?v=vPfN2BnnpUc
From Data to Knowledge - 106 - Sotiria Lampoudi
Slides: http://lyra.berkeley.edu/CDIConf/pdfs/Lampoudi_Berkeley2012.pdf Sotiria Lampoudi: "Bounds estimation from timeseries". A video from the UC Berkeley Conference: From Data to Knowledge: Machine-Learning with Real-time and Streaming Applications (May 7-11, 2012). Abstract Sotiria Lampoudi (UC Santa Barbara, CS) QBETS (http://spinner.cs.ucsb.edu/batchq/) is a service for estimating bounds on the wait times of jobs submitted to batch queued supercomputers. QBETS is formed by a binomial non-parametric statistical method at the core, wrapped in a time series clustering method with change-point detection. We are in the process of re-engineering QBETS to work on generic, as opposed to domain-specific, time series, and are continually improving the underlying methodology.
Views: 216 ckleinastro
Convert SPSS (.sav) to Text (.csv)
Short video on how to convert SPSS data files to CSV using R library(foreign) mydata = read.spss("C:\\Find\\Your\\File\\File.sav",to.data.frame=TRUE) write.table(mydata,"mydataFormR.txt") getwd()
Views: 55927 Michael Herman
Build A Classification Model In Random Forests
http://www.salford-systems.com This 15-minute video tutorial will teach you everything you need to know to build your first classification model using Random Forests. Random Forests is a bagging tool that leverages the power of multiple alternative analysis, randomization strategies, and ensemble learning to produce accurate models, insightful variable importance ranking, and laser-sharp reporting on record-by-record basis for deep data understanding.
Views: 28333 Salford Systems
Peterbilt Atlantic Tech Tips: Dashboard Indicators & Warning Lights
Shawn Warman highights the meanings of the varous dashboard indicators lights in a Peterbilt truck. Visit Peterbilt Atlantic online anytime at http://www.PeterbiltAtlantic.com
Views: 65129 peterbiltatlantic
Data Management: Best Practices for Producing High Quality Data (INQUIRE Webinar #3)
The purpose of this INQUIRE webinar is to provide an overview of best practices in data management for early childhood data, specifically QRIS.
Views: 778 Child Trends
Archiving Data with ADDEP (the Archive of Data on Disability to Enable Policy and research
Archive director Amy Pienta describes the steps to successfully archive research with the Archive of Data on Disability to Enable Policy and research (ADDEP) at ICPSR. The webinar shares best practices to assist researchers in the preparation of their data for use by their own project team and the research community, reviewing the deposit form and guidelines, data access options, and viewing a brief demonstration of the resources available through the ADDEP website. This webinar was originally broadcast on December 1, 2016. Here is a link to download webinar slides: http://www.icpsr.umich.edu/files/videos/ADDEPDec0116.pptx
Views: 243 ICPSR
AdWords tutorial from Google - Step 1: What you need to know about online marketing
Google AdWords is now Google Ads. Click here to learn more about our new advertising brand: blog.google/technology/ads/new-advertising-brands/ Before you take advantage of all that online marketing can do for your business, make sure you know the basics. Links: Continue to Step 2: Reach more customers: https://www.youtube.com/watch?v=B36zZ1uiPkI&list=PL9piTIvKJnJPB729hcZYSEXCsQFyeJV44&index=2
Views: 324922 Google Ads
Joe Kutchera "EXITO: The 5 factors of success for digital marketing" | Authors at Google
"Author Joe Kutchera will outline his 5-step marketing process for reaching the next generation of Internet users in the booming markets of Latin America. See Rodrigo's [email protected] here: http://youtu.be/6yrEsYs24_o About the Author: Joe Kutchera advises companies on how to best develop culturally customized content for social media, newsletters and websites. He is the author of two books including Latino Link: Building brands online with Hispanic communities and content and has been featured as a thought-leader on Advertising Age, BBC Mundo, CNN en español, NBC Latino, and Telemundo. Joe writes for Fox News Latino and has served as a board member for the Interactive Advertising Bureau (IAB) Mexico and as a member of the Hispanic Committee for the IAB in the U.S. During his nine-year tenure at Time Warner, he built some of its leading web properties including Time Inc Mexico where he launched CNNExpansion, the largest business news site in Mexico, and started its digital ad sales team. Subsequently, he launched ContextWeb's Spanish-language ad network in the U.S. and Mexico. Kutchera has spoken throughout the U.S., Spain, and Mexico at conferences and universities. Kutchera holds an MBA from Fordham University in New York City. A free sample chapter of his book is available at: http://JoeKutchera.com"
Views: 2481 Talks at Google
Hvordan strikke en vrangbordlue / How to knit a ribbed hat / Prym Maxi knitting mill
Her viser jeg hvordan du kan strikke en vrangbordlue på en prym maxi strikkemølle. Jeg har strikket med bomullsgarn innerst (Mandarin Petit fra Sandens Garn) og ullgarn ytterst (Alfa fra Sandnes Garn). Luen jeg strikket ble i størrelse 2-3 år. This is how you can knit a ribbed hat on a prym maxi knitting mill. I have knitted it double, with cotton on the inside and wool on the outside. The size is about 2-3 years. Besøk gjerne bloggen min / Visit my blog http://www.tidtilovers.com
Views: 11153 Ingunn Hvattum
Please support Peter Joseph's new, upcoming film project: "InterReflections" by joining the mailing list and helping: http://www.interreflectionsmovie.com LIKE Peter Joseph @ https://www.facebook.com/peterjosephofficial FOLLOW Peter Joseph @ https://twitter.com/ZeitgeistFilm * Sign up for TZM Mailing List: http://www.thezeitgeistmovement.com/ Sign up for the Film Series Mailing List: http://zeitgeistmovie.com/ This is the Official Online (Youtube) Release of "Zeitgeist: Moving Forward" by Peter Joseph. [30 subtitles ADDED!] On Jan. 15th, 2011, "Zeitgeist: Moving Forward" was released theatrically to sold out crowds in 60 countries; 31 languages; 295 cities and 341 Venues. It has been noted as the largest non-profit independent film release in history. This is a non-commercial work and is available online for free viewing and no restrictions apply to uploading/download/posting/linking - as long as no money is exchanged. A Free DVD Torrent of the full 2 hr and 42 min film in 30 languages is also made available through the main website [below], with instructions on how one can download and burn the movie to DVD themselves. His other films are also freely available in this format. Website: http://www.zeitgeistmovingforward.com http://www.zeitgeistmovie.com SUPPORT PETER JOSEPH (DONATIONS): http://zeitgeistmovie.com/torrents.html Release Map: http://zeitgeistmovingforward.com/zmap DVD: http://zeitgeistmovie.com/order.html Movement: http://www.thezeitgeistmovement.com Subtitles provided by Linguistic Team International: http://forum.linguisticteam.org/
Views: 24991804 TZMOfficialChannel
Auburn Coach Wife Kristi Malzahn Agrees with Match & eHarmony: Men are Jerks
My advice is this: Settle! That's right. Don't worry about passion or intense connection. Don't nix a guy based on his annoying habit of yelling "Bravo!" in movie theaters. Overlook his halitosis or abysmal sense of aesthetics. Because if you want to have the infrastructure in place to have a family, settling is the way to go. Based on my observations, in fact, settling will probably make you happier in the long run, since many of those who marry with great expectations become more disillusioned with each passing year. (It's hard to maintain that level of zing when the conversation morphs into discussions about who's changing the diapers or balancing the checkbook.) Obviously, I wasn't always an advocate of settling. In fact, it took not settling to make me realize that settling is the better option, and even though settling is a rampant phenomenon, talking about it in a positive light makes people profoundly uncomfortable. Whenever I make the case for settling, people look at me with creased brows of disapproval or frowns of disappointment, the way a child might look at an older sibling who just informed her that Jerry's Kids aren't going to walk, even if you send them money. It's not only politically incorrect to get behind settling, it's downright un-American. Our culture tells us to keep our eyes on the prize (while our mothers, who know better, tell us not to be so picky), and the theme of holding out for true love (whatever that is—look at the divorce rate) permeates our collective mentality. Even situation comedies, starting in the 1970s with The Mary Tyler Moore Show and going all the way to Friends, feature endearing single women in the dating trenches, and there's supposed to be something romantic and even heroic about their search for true love. Of course, the crucial difference is that, whereas the earlier series begins after Mary has been jilted by her fiancé, the more modern-day Friends opens as Rachel Green leaves her nice-guy orthodontist fiancé at the altar simply because she isn't feeling it. But either way, in episode after episode, as both women continue to be unlucky in love, settling starts to look pretty darn appealing. Mary is supposed to be contentedly independent and fulfilled by her newsroom family, but in fact her life seems lonely. Are we to assume that at the end of the series, Mary, by then in her late 30s, found her soul mate after the lights in the newsroom went out and her work family was disbanded? If her experience was anything like mine or that of my single friends, it's unlikely. And while Rachel and her supposed soul mate, Ross, finally get together (for the umpteenth time) in the finale of Friends, do we feel confident that she'll be happier with Ross than she would have been had she settled down with Barry, the orthodontist, 10 years earlier? She and Ross have passion but have never had long-term stability, and the fireworks she experiences with him but not with Barry might actually turn out to be a liability, given how many times their relationship has already gone up in flames. It's equally questionable whether Sex and the City's Carrie Bradshaw, who cheated on her kindhearted and generous boyfriend, Aidan, only to end up with the more exciting but self-absorbed Mr. Big, will be better off in the framework of marriage and family. (Some time after the breakup, when Carrie ran into Aidan on the street, he was carrying his infant in a Baby Björn. Can anyone imagine Mr. Big walking around with a Björn?)
Views: 202736 Shari Wing