A colleague posted a Christmas-themed code snippet that shows how to use the DATA step in SAS to output all the possible ways that Santa can hitch up a team of reindeer to pull his sled. The assumption is that Rudolph must lead the team, and the remaining reindeer are
Vor gut zwei Jahren hat die für den DACH-Raum (Deutschland, Österreich, Schweiz) zuständige Niederlassung des US-amerikanischen Software-Herstellers SAS Institute begonnen agile Methoden im Software-Vertrieb einzusetzen. Die Hauptmotivation für den damaligen Start der Initiative lag in der Hebung ungenutzter Potentiale im Zusammenhang mit der Generierung von Neugeschäft (auch als Demand- bzw.
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SAS' Bahar Biller expounds on the idea that stochastic simulations are large-data generation programs for highly complex and dynamic stochastic systems.
대표적인 오픈소스인 R, 파이썬 사용자들이 SAS 제품의 성능과 장점을 쉽게 활용할 수 있는 방법은 무엇일까요? 오픈소스 사용자들은 SAS에 어떻게 접근을 해서 어떠한 결과물을 만들어낼 수 있을까요? 데이터 분석에 대한 가장 폭넓은 시각과 라이프사이클 솔루션을 보유한 SAS만의 데이터분석 능력을 오픈 소스를 선호하는 R, 파이썬 사용자들도 쉽게 활용할 수 있는 방법을 소개해
A previous article describes how to use SAS IML software to construct common covariance structures that are encountered in mixed models. Each covariance matrix has several parameters, and you want to construct a matrix for any choice of the parameters. After you have constructed the covariance matrix, you can use
The landscape of supply chains has changed rapidly due to unforeseen disruptions. These changes include supply chain bottlenecks, inflation and geopolitical activities across retail and consumer goods industries. Retail supply chains are under immense pressure to keep up with these rapid changes. Innovators have been quick to take advantage of
증가하는 AI 시스템 구축 최근 AI 시스템 구축에 관한 기사들을 많이 볼 수 있습니다. 국민은행의 AI 보이스피싱 모니터링 시스템, 심평원의 인공지능(AI)을 이용한 과잉 진료 단속 시스템, 우리은행의 무역 기반 자금세탁방지(Anti-TBML) 시스템, 대우건설의 AI 기반 입찰 데이터 분석 시스템, 그리고 갤러리아 백화점의 AI 기반 백화점 맞춤서비스 등 매우 다양합니다. 이러한 AI
I always emphasize efficiency in statistical programming. I have previously written about why you should never multiply with a large diagonal matrix in the SAS IML language. The reason is that it is more efficient to use elementwise multiplication than matrix multiplication. Specifically, if d is a column vector, then
SAS 바이야(Viya)의 자동 머신 러닝으로 현업 담당자도 손쉽게 데이터 분석 가능 인공지능(AI)과 머신 러닝(ML)이 등장하기 시작한 약 10 여 년 전부터 Data Science 영역이 많은 주목을 받게 되었고, 이에 따라 급여가 높고 장래성이 있는 매력적인 직업으로서 Data Scientist의 인기가 한층 높아지고 있습니다. Data Scientist의 역할을 제대로 수행하기 위해서는 컴퓨터 프로그램
一、背景の紹介 SAS Viyaに搭載されているSAS StudioはSASプログラムの作成と実行のツールとしてよくユーザーさんたちに利用されています。また、実際のビジネスの中では、SASプログラムのバッチ実行が必要となる場面もたくさん存在しています。しかし、多くのSAS９を活用している既存のユーザーは、Viyaでのバッチ実行方式に対してまだ詳しくないかもしれませんので、本ブログを通してViyaでバッチ方式でのSASプログラムの実行方法を紹介したいと思います。 以下は本記事内容の一覧です。読者は以下のリンクをで興味のあるセクションに直接ジャンプすることができます。 二、sas-viya CLIツールの紹介 １．sas-viya CLIとは ２．インストール方法の紹介 三、SASプログラムをバッチで実行する方法の紹介 １．バッチでSASプログラムの実行 ２．実行されたバッチジョブの確認とログの取得方法 ３．バッチジョブの削除と停止方法 二、sas-viya CLIツールの紹介 １．sas-viya CLIとは SAS Viyaのコマンドラインインターフェース（以下はsas-viya CLI）は、コマンドライン上で、SAS ViyaのRESTサービスを利用することによって、SAS Viyaの設定や機能を利用するためのツールです。CLIは、グラフィカル・ユーザー・インターフェース（GUI）を使用する代わりに、プログラム的にSAS Viyaを操作するために使用することができます。 sas-viya CLIのbatchプラグインは、SAS Viya環境にコマンドラインからSASプログラムやコマンドをアップロードし、バッチ処理することを可能にします。プログラムをアップロードした後は、サーバ側でバッチ処理を実施するので、処理中にViyaのサーバとの接続を維持する必要はありません。 ２．インストール方法の紹介 従来SAS9を利用しているユーザーは、sas.exeなどでSASプログラムをバッチで実行していたと思いますが、Viyaの場合はsas-viyaというコマンドラインツールを利用します。別途でインストールは必要ですが、Viyaのサービスへ接続できるところであれば、WindowsでもLinuxでも、任意のマシン上から遠隔でViya上でSASジョブの実行ができます。以下ではsas-viyaコマンドラインツールのインストールとセットアップ方法を紹介します。 まずは下記のサイトからお使いのOS(Linux, Window, OSX)に応じて、インストールファイルをダウンロードします。 https://support.sas.com/downloads/package.htm?pid=2512/ ① Windowsをご利用の場合の手順は以下となります。Linuxユーザーの方は、こちらを参照ください。 (1)ダウンロードしたzipファイルを解凍し、sas-viya.exeのフォルダの下にshift+右クリックし、「PowelShellウィンドウをここで開く」をクリックします。 (2)利用開始の前に、接続先のViyaサーバ情報の初期登録が必要ですので、下記のコマンドを実行します。聞かれた内容を下記のように入力し、アクセス先を定義します。 .sas-viya.exe profile init こちらのステップは初めて利用する際に、一回だけ実施します。Service Endpointは繋ぎ先のURLを入力し、それ以外の”Output type”と”Enable ANSI colored output”については、画面に出力されたメッセージのフォーマットを指定するものですので、お好みの設定で構いません。もしわからない場合は、それぞれにtextとyにすれば良いです。 (3)接続先の情報を設定し終わったら、次はサーバへのログインです。下記のコマンドを実行して、IDとPWを入力し、ログインします。 .sas-viya auth login
Building on a previous post on how the seqmc action can be used to mine frequent sequences, SAS' Amod Ankulkar explores an alternative algorithm.
For Christmas 2021, I wrote an article about palettes of Christmas colors, chiefly shades of red, green, silver, and gold. One of my readers joked that she would like to use my custom palette to design her own Christmas wrapping paper! I remembered her jest when I saw some artwork
The ultimate objective of a churn model is preventing churn by making a retention offer. To determine reasonable values for profit and loss information, consider the outcomes and the actions that you would take given knowledge of these outcomes. For example, the marketing department of a telecommunications company wants to offer a discount to people who are no longer on a fixed-term contract. To prevent churn, the company is willing to make an offer in exchange for a one-year contract extension.
A probabilistic card trick is a trick that succeeds with high probability and does not require any skill from the person performing the trick. I have seen a certain trick mentioned several times on social media. I call it "ladders" or the "ladders game" because it reminds me of the
Whether you’re looking for technical or business opportunities, a strong resume will help you stand out from the crowd and make a good first impression. But resume creation is an art, not a science, and starting from scratch can feel daunting. Never fear – our Talent Acquisition Specialist, Christie Eades,
A SAS programmer was trying to simulate poker hands. He was having difficulty because the sampling scheme for simulating card games requires that you sample without replacement for each hand. In statistics, this is called "simple random sampling." If done properly, it is straightforward to simulate poker hands in SAS.
Este recurso está diseñado principalmente para científicos de datos, analistas principiantes o intermedios que están interesados en identificar y aplicar algoritmos de machine learning para abordar los problemas de su interés. Una pregunta típica de un principiante, cuando se enfrenta a una gran variedad de algoritmos de machine learning, es:
Change is one of the few constants in our fast-moving world. Organisations must respond rapidly and effectively to changes in their environment, including among their customers. Being able to address new problems and issues, especially at speed, means that innovation is now essential for companies to survive and thrive. However,
The advantage of using SAS PROC KPCA is that you can preprocess your data so that you can classify groups with nonlinear classification boundaries.
스마트폰 대중화로 모바일 광고 시장은 애드테크(Ad-Tech) 타겟 광고를 기반으로 약 800억 달러 규모로 성장하였으나, 사용자의 행동 정보를 동의 없이 사용하는 광고 생태계의 프로세스로 인해 개인정보 이슈를 가중시켰습니다. 최근 메타(페이스북 모기업)의 주가가 하루사이에 26% 넘게 폭락하였으며, 이는 메타의 실적 부진과 영업이익의 하락이 원인이었습니다. 메타의 경우 전체 매출의 98% 가량이 광고사업에서 나오고
Recently, I needed to know "how much" of a piecewise linear curve is below the X axis. The coordinates of the curve were given as a set of ordered pairs (x1,y1), (x2,y2), ..., (xn, yn). The question is vague, so the first step is to define the question better. Should
Billy Dickerson of SAS R&D chronicles three key challenges and lessons learned in SAS' journey to continuous integration (CI) and continuous delivery (CD).
A profile plot is a way to display multivariate values for many subjects. The optimal linear profile plot was introduced by John Hartigan in his book Clustering Algorithms (1975). In Michael Friendly's book (SAS System for Statistical Graphics, 1991), Friendly shows how to construct an optimal linear profile by using
사회의 모든 측면에서 인공 지능(AI) 채택이 급격히 증가함에 따라 윤리는 기술의 새로운 프론티어임이 입증되고 있습니다. 대중의 인식, 언론 조사 및 향후 규정으로 인해 조직과 데이터 과학 커뮤니티는 AI 사용의 윤리적 의미를 고려해야 합니다. 인적 요소를 고려하고 비즈니스 결과에 기여할 뿐만 아니라 개인, 사회 및 환경을 보호하는 AI 시스템을 개발할 필요성을
A profile plot is a compact way to visualize many variables for a set of subjects. It enables you to investigate which subjects are similar to or different from other subjects. Visually, a profile plot can take many forms. This article shows several profile plots: a line plot of the
SAS® Fast-KPCA implementation bypasses the limitations of exact KPCA methods. SAS® internally uses k-means to find a representative sample of a subset of points. This row reduction method has the advantage that c centroids are chosen to minimize the variation of points nearest to each centroid and maximize the variation to the other cluster centroids. In some cases, the downstream effect of using k-means on computing the SVD increases numerical stability and improves clustering, discrimination, and classification.
More digital channels are bringing greater connectivity and more data is bringing added complexity to organizations. All this can feel chaotic or like a fog of information warfare. As a result, the pace of disruption and data expansion require visual tools that accelerate data wrangling and modeling. To overcome complexity,
공원을 걷다 보면 좋아하는 운동을 하는 아이들을 흔히 볼 수 있습니다. 그들은 종종 기술을 연마하기 위해 오랜 시간을 보냅니다. 그러나 혼자서는 무엇을 어떻게 해야 현재를 개선해야 하는지 파악하기 어렵습니다. 좀 더 나은 수준으로 향상하기 위해서는 무엇을 해야 하는지 가르칠 수 있는 코치를 고용하면 좋겠는데, 그렇게 하는 것은 비용이 많이 듭니다. 이럴 때 어떤 대안이
SAS' Yogender Kushawah introduces you to mining long sequences efficiently using the seqmc action in SAS Visual Analytics.
