夏といえばひまわり。鮮やかな黄色は一輪でも強い存在感を放ち、我が家の食卓を飾る花でもある。ひまわりの花は常に太陽に向かって咲き、時間とともに太陽を追いかけるとされている。しかし、実際にはこのように動くのは芽生えから開花前のつぼみの時期までの話だ。 自然界にあるひまわりの成長には、太陽、気温、降水量、土壌など多くの要因が影響するが、これらの要因がどう関係するのだろうか。人工的な実験でも可能だが、たとえばひまわりの成長データを収集し、統計分析を用いることで最適な成長条件や栽培環境が特定できるはずだ。また、ビッグデータならではの機械学習アルゴリズムを使えば成長のルールやパターンを見つけることもできる。アナリティクスを駆使すれば(SASで開講中のアナリティクスコースはこちら⇒トレーニングコース | SAS)、収穫量の予測や最適な施肥方法、栽培条件も見つけられるだろう。実際、ひまわりの市場は世界で5.6兆円に登る巨大なマーケットなのだ。 ところで、ひまわりといえば気象衛星を連想するのは私だけだろうか。初代号が1977年に打ち上げられ、今度が10号になるが、最初は愛称で呼ばれていたものが後に正式名称となった。気象庁のサイト(気象庁 Japan Meteorological Agency)では、ほぼリアルタイムでひまわりの衛星写真がさまざまな切り口から見られるが、天気や防災に関する情報のほか、上記のような分析に欠かせない環境や気象のデータも豊富に提供されている。 2024年9月初旬 相吉
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In SAS, DATA step programmers use the IN operator to determine whether a value is contained in a set of target values. Did you know that there is a similar functionality in the SAS IML language? The ELEMENT function in the SAS IML language is similar to the IN operator
A previous article shows how to implement recursive formulas in SAS. The article points out that you can often avoid recursion by using an iterative algorithm, which is more efficient. An example is the Fibonacci sequence, which is usually defined recursively as F(n) = F(n-1) + F(n-2) for n
Many well-known distributions become more and more "normal looking" for large values of a parameter. Famously, the binomial distribution, Binom(p, N), can be approximated by a normal distribution when N (the sample size) is large. Similarly, the Poisson(λ) distribution is well approximated by the normal distribution when λ is large.
SAS와 같은 글로벌 기업이 비즈니스를 할 때에는 글로벌 관점과 현지 관점의 균형을 맞추는 것이 중요합니다. 제품은 글로벌 시장 전반에 걸쳐 제공되어야 하고, 글로벌 경쟁력을 갖춰야 합니다. 반면, 고객과의 관계 구축은 현지 상황에 맞아야 합니다. 이는 적절한 현지 파트너와 협력을 통해서 강화할 수 있습니다. SAS코리아와 오랜 세월을 함께 동행해온 든든한 파트너,
As part of this year's IEEE Visual Analytics Science and Technology (VAST) Challenge, a group of SAS data scientists puit SAS Viya and related machine learning tools to the ultimate test - to identify individuals in a complex fishing network. Excitedly, the team received the Honorable Mention Award for Breadth of Investigation!
There are two programming tools that I rarely use: the SAS macro language and recursion. The SAS macro language is a tool that enables you to generate SAS statements. I rarely use the SAS macro language because the SAS IML language supports all the functionality required to write complex programs,
The SAS IML Language has a quirk with regards to functions that take no arguments. As discussed in the documentation, "modules with arguments are given a local symbol table." This is the usual behavior that programmers expect. However, the documentation goes on to state that "a module that has no
幼い頃、家の庭にたくさんのバラがあり、手入れが大変だった思いがある。トゲに刺されて痛い思いをしたり、傷になったりしたことを覚えている。興味深いことに、統計学の歴史にはナイチンゲールの「バラ」というグラフが登場する。 「白衣の天使」として知られるイギリスの看護師フロレンス・ナイチンゲールは、優れた統計学者でもあった。彼女は19世紀のクリミア戦争で看護師として派遣され、膨大な戦死者・傷病者データを分析し、多くの兵士が戦傷ではなく劣悪な衛生状態のために命を落としていることを明らかにした。その後、政治や行政に向けに「ローズダイアグラム」という革新的なグラフで報告した。 ローズダイアグラムは、円グラフの一種で、死因を視覚的に示すチャートである。月ごとの死亡者数を戦傷を赤、衛生状態や栄養不足を青、その他の要因を黒で色分けし、それぞれの面積で表現したものである(Florence Nightingale's Rose Diagram)。このグラフにより、衛生改善の必要性が明確になり、医療環境の改善が進んで傷病兵の死亡率が大幅に減少したのは言うまでもない。 統計学は記述統計と推測統計に分かれ、記述統計はデータの特徴を分かりやすく表現することを目的とする。ナイチンゲールの事例は、記述統計とデータ可視化が如何に重要かを物語っている。SASには「SAS Visual Analytics」という優れた可視化ツールがあり、基礎から上級までの関連コースも提供されている(SASトレーニングコース)。 2024年8月初旬 相吉
In SAS, the easiest way to draw random sampling from data is to use PROC SURVEYSELECT or the SAMPLE function in SAS IML software. I have previously written about how to implement four common sampling schemes by using PROC SURVEYSELECT and the SAMPLE function. The DATA step in SAS is
What sets the SAS Model Card apart from previous model cards is the use of descriptive visuals, to make model cards accessible to all personas involved in the analytics process, including data scientists, data engineers, MLOPs engineers, managers, executives, risk managers, business analytics, end-users, and any other stakeholder with access to the SAS Viya environment.
This article shows how to simulate data from a Poisson regression model, including how to account for an offset variable. If you are not familiar with how to run a Poisson regression in SAS, see the article "Poisson regression in SAS." A Poisson regression model is a specific type of
When using LLMs, managing toxicity, bias, and bad actors is critical for trustworthy outcomes. Let’s explore what organizations should be thinking about when addressing these important areas.
This article demonstrates how to use PROC GENMOD to perform a Poisson regression in SAS. There are different examples in the SAS documentation and in conference papers, but I chose this example because it uses two categorical explanatory variables. Therefore, the Poisson regression can be visualized by using a contingency
Learn how an intern integrated SAS Viya® and open-source code (Python) into a Machine Learning project to combine their strengths within the context of predictive modeling, and to show off the variety of ways this integration can be accomplished.
An article published in Nature has the intriguing title, "AI models collapse when trained on recursively generated data." (Shumailov, et al., 2024). The article is quite readable, but I also recommend a less technical overview of the result: "AI models fed AI-generated data quickly spew nonsense" (Gibney, 2024). The Gibney
Learn how to use SAS code (PROC HTTP) to read and write files from your Microsoft OneDrive, Microsoft Teams or SharePoint Online. You'll learn how to create a Microsoft Office 365 app, connect to it with SAS, and automate the integration with your office productivity environment.
A previous article shows that you can run a simple (one-variable) isotonic regression by using a quadratic programming (QP) formulation. While I was reading a book about computational geometry, I learned that there is a connection between isotonic regression and the convex hull of a certain set of points. Whaaaaat?
Since the pandemic began in 2020, the SAS IML developers have added about 50 new functions and enhancements to the SAS IML language in SAS Viya. Among these functions are new modern methods for optimization that have a simplified syntax as compared to the older 'NLP' functions that are available
Where GPT-4o is concerned for computer vision, SAS' Jonny McElhinney, Julia Florou-Moreno, and Priti Upadhyay advocate a trust-but-verify approach.
What's the difference between LENGTH and FORMAT in a SAS data set? This article shares the answer, with examples.
기업내에 AI/ML를 적용하기 위해, 업무 관점에서 시민 데이터 사이언티스트(Citizen Data Scientist, 이하 CDS)와 그 필요 역량인 데이터 문해력(Data Literacy)의 중요성이 높아지고 있습니다.(참고 : 데이터 문해력과 시민 데이터 사이언티스트의 필요 역량) 이와 연결하여, 데이터를 기반으로 신속하게 개발한 예측 모델을 업무 시스템에 통합 또는 활용하기 위해 IT 관점에서 해결해야할 과제와 접근 방안에 대해
Just like the SAS DATA step, the SAS IML language supports both functions and subroutines. A function returns a value, so the calling syntax is familiar: y = func(x1, x2); /* the function returns one value, y */ In this syntax, the input arguments are x1 and x2. The
생성형 AI에 대한 전세계 기업들의 투자와 활용이 계속되는 가운데, 이와 관련된 흥미로운 조사 결과가 발표되었습니다. SAS가 최근 콜먼 파크스 리서치(Coleman Parkes Research Ltd.)에 의뢰한 전세계 조사에 따르면 생성형 AI를 가장 적극적으로 사용하고 있는 나라는 중국인 것으로 나타났습니다. 중국의 비즈니스 의사 결정자들은 자사 조직의 83%가 이 기술을 이용하고 있다고 응답했습니다. 이는
A recent article came out with an updated list of necessary components for MLOps and LLMOps. And while this list may seem long, reading through the capabilities and components, I realized that SAS Viya already covers most of the required functionality. Organizations can have a hodgepodge of tools that they
Isotonic regression (also called monotonic regression) is a type of regression model that assumes that the response variable is a monotonic function of the explanatory variable(s). The model can be nondecreasing or nonincreasing. Certain physical and biological processes can be analyzed by using an isotonic regression model. For example, a
Emojis are showing up in our data. Here's what you need to know when working with emojis in your SAS code.
この時期の私の楽しみは、散歩の途中でかわいらしい色とりどりのアジサイの花を眺めることだ。アジサイは、「集まる」や「寄せ集める」という意味があり、花弁がいくつも集まっている咲き姿に由来しているそうだ。別名「七変化」とも呼ばれており、土の性質によって花色が変わるのが特徴。土が酸性だとブルー系、中性からアルカリ性だとピンク系になるそうだ。面白いことに、ブルーのアジサイをアルカリ性の土に植え替えると薄紫色のアジサイに変化するそうだ。 「統計学と機械学習の違いは何か」という質問を受けることがある。土の性質で色が変わるアジサイのように、機械学習と統計学も同じような関係ではないかと思う。両者の目的は似ているが、ビッグデータと高度な計算能力という土俵の違いが機械学習の発展に大きく寄与したのは間違いない。ただ、機械学習の歴史は比較的新しいが、統計学がなければその発展は考えにくい。例えば、決定木分析は機械学習が流行る前から統計学の手法の一つだったが、機械学習の進展とともに進化してきた。ちなみに決定木分析は樹形図の形式で結果を出力し、そのため初心者でも理解しやすい分析手法の一つ。SASでは、機械学習をはじめとして、ニューラルネットワーク、AI関連のトレーニングコースが年に数回開催されている(SASトレーニングコース)。 ※Google Trendによると日本での検索数は、2016年当りから交差する形で機械学習が統計学を上回るようになった。機械学習が統計学より広まったのは、ビジネスパーソンであろうが消費者であろうが、意思決定の場面で使われる頻度や処理速度に関連があると思う。 2024年7月初旬 相吉
A previous article discusses the fact that there are often multiple ways in SAS to obtain the same result. This fact results in many vigorous discussions on online programming forums as people propose different (but equivalent) methods for solving someone's problem then argue why their preferred method is better than
Adding linguistic techniques in SAS NLP with LLMs not only help address quality issues in text data, but since they can incorporate subject matter expertise, they give organizations a tremendous amount of control over their corpora.