One of the benefits of social media is the opportunity to learn new things. Recently, I saw a post on Twitter that intrigued me. The tweet said that the expected volume of a random tetrahedron in the unit cube (in 3-D) is E[Volume] = 0.0138427757.... This number seems surprisingly small!
Have you ever typed your credit card into an online order form and been told that you entered the wrong number? Perhaps you wondered, "How do they know that the numbers I typed do not make a valid credit card number?" The answer is that credit card numbers and other
La analítica de datos es conocida porque permite detectar patrones y comportamientos para predecir situaciones. Gracias a ella, las instituciones tienen la capacidad de anticiparse a las necesidades de los ciudadanos y poder tomar decisiones. Otra de las aplicaciones que tiene para, por ejemplo, las marcas, es poder recomendar productos
Getting demand right – or getting it wrong – can have a significant impact on customer perceptions of your brand, particularly in this age of instant gratification. The need for agile, accurate demand planning has never been greater. Predicting forward-looking demand signals and shifting consumer demand patterns to recommend balanced, profitable commercial
To find exact duplicates, matching all string pairs is the simplest approach, but it is not a very efficient or sufficient technique. Using the MD5 or SHA-1 hash algorithms can get us a correct outcome with a faster speed, yet near-duplicates would still not be on the radar. Text similarity is useful for finding files that look alike. There are various approaches to this and each of them has its own way to define documents that are considered duplicates. Furthermore, the definition of duplicate documents has implications for the type of processing and the results produced. Below are some of the options. Using SAS Visual Text Analytics, you can customize and accomplish this task during your corpus analysis journey either with Python SWAT package or with PROC SQL in SAS.
SAS' multidimensional culture blends our different backgrounds, experiences and perspectives from employees in 59 countries worldwide. We want everyone to feel confident expressing their ideas and know they will be respected for their unique contributions and abilities. At SAS, it’s not about fitting into our culture; it’s about adding to
A previous article discusses the definitions of three kinds of moments for a continuous probability distribution: raw moments, central moments, and standardized moments. These are defined in terms of integrals over the support of the distribution. Moments are connected to the familiar shape features of a distribution: the mean, variance,
Using SAS Viya in combination with open-source capabilities, we were able to develop an automated solution for logo detection that does not require any manual data labeling.
SAS is excited to announce our inaugural Customer Appreciation Awards. We want to give a big “thank you” and a round of applause to all our SAS customers and partners around the globe who help us change the world through analytics. We want to recognize a few of you for
It was the summer of ’22. And in the words of Taylor Swift, “I remember it all too well” (Taylor’s version, of course). From mentoring opportunities, networking with top leaders and other interns, exploring our culture that promotes well-being and work-life integration to having meaningful work to gain real world
September honors Recovery Month, emphasizing hope for recovery in behavioral health, especially from substance use disorders (SUD). A key motto of Recovery Month is that Recovery Happens, helping people know that even at rock bottom, things can improve. We all need that hope at various points in our lives. Often,
Crises like the COVID-19 pandemic have increased the demand for public health experts who possess advanced analytics skills. After all, data – when properly collected, analyzed and understood – has immense power to inform decision-making. And in areas like public health, informed decision making can save lives. Azhar Nizam has
The moments of a continuous probability distribution are often used to describe the shape of the probability density function (PDF). The first four moments (if they exist) are well known because they correspond to familiar descriptive statistics: The first raw moment is the mean of a distribution. For a random
A strong cultural emphasis on “happiness” can have the unintended effect of casting feelings other than happiness as being bad or something to avoid. But life is rich with many different feelings. Trying to suppress these can actually lead to a rebound effect. The book Get Out of Your Mind
The correlations between p variables are usually displayed by using a symmetric p x p matrix of correlations. However, sometimes you might prefer to see the correlations listed in "long form" as a three-column table, as shown to the right. In this table, each row shows a pair of variables and the
You’re down by 10 points in your NFL fantasy football league, and you need to choose a wide receiver from the free agency pool because your starter was injured. How do you decide to get the 11 points required for a win? What methods will you use to lead you
Even with today's technology, it's hard to know precisely when, where and how weather-related damage will occur. Flooding costs are expected to rise drastically during the next 20 years and climate change is a constant threat. Unfortunately, natural disasters are here to stay, but we can try our best to
The noncentral t distribution is a probability distribution that is used in power analysis and hypothesis testing. The distribution generalizes the Student t distribution by adding a noncentrality parameter, δ. When δ=0, the noncentral t distribution is the usual (central) t distribution, which is a symmetric distribution. When δ >
こんにちは！SAS Institute Japanの堀内です。今回も自然言語処理について紹介いたします。 前回の投稿では、実際にSASを使って日本語の文章を扱う自然言語処理の例を解説しました。 最終回の本投稿ではその応用編として、自然言語処理の代表的なタスクとSASによる実装方法を紹介します。なお、ここでいうタスクとは「定式化され一般に共有された課題」といった意味になります。自然言語処理には複数のタスクがあり、タスクごとに、共通する部分はあるとはいえ、問題解決のアプローチ方法は基本的に大きく異なります。SASには各タスクごとに専用のアクションセット1が容易されています。 要約タスク その名の通り文章を要約するタスクです。SASではtextSummarizeアクションセットで対応可能です。 ここでは、NHKのニュース解説記事「気になる頭痛・めまい 天気が影響？対処法は？」(https://www.nhk.or.jp/kaisetsu-blog/700/471220.html) の本文を５センテンスで要約してみましょう。 import swat conn = swat.CAS('mycashost.com', 5570, 'username', 'password') conn.builtins.loadActionSet(actionSet='textSummarization') conn.textSummarization.textSummarize(addEllipses=False, corpusSummaries=dict(name='corpusSummaries', compress=False, replace=True), documentSummaries=dict(name='documentSummaries', compress=False, replace=True), id='Id', numberOfSentences=5, table={'name':CFG.in_cas_table_name}, text='text', useTerms=True, language='JAPANESE') conn.table.fetch(table={'name': 'corpusSummaries'}) numberOfSentencesで要約文のセンテンス数を指定しています。結果は以下の通りです。 'まず体調の変化や天気、気温・湿度・気圧などの日記をつけ、本当に天気が影響しているのか、どういうときに不調になるのかパターンを把握すると役立ちます。 気温・湿度以外にも、気圧が、体調の悪化や、ときに病気の引き金になることもあります。 私たちの体は、いつも耳の奥にある内耳にあると言われている気圧センサーで、気圧の変化を調整しています。 ただ、天気の体への影響を研究している愛知医科大学佐藤客員教授にお話ししを伺ったところ、「台風最接近の前、つまり、気圧が大きく低下する前に、頭が痛いなど体調が悪くなる人は多い」ということです。 内耳が敏感な人は、わずかな気圧の変化で過剰に反応し、脳にその情報を伝えるので、脳がストレスを感じ、体のバランスを整える自律神経が乱れ、血管が収縮したり、筋肉が緊張するなどして、その結果、頭痛・めまいなどの体に様々な不調につながっているのです。' 重要なセンテンスが抽出されていることが分かります。 テキスト分類タスク 文章をいくつかのカテゴリに分類するタスクです。その内、文章の印象がポジティブなのかネガティブなのか分類するものをセンチメント分析と呼びます。ここでは日本語の有価証券報告書の文章をポジティブかネガティブか判定してみます。使用するデータセットは以下になります。 https://github.com/chakki-works/chABSA-dataset （なお、こちらのデータセットには文章ごとにポジティブかネガティブかを示す教師ラベルは元々付与されておりませんが、文章内の特定のフレーズごとに付与されているスコアを合算することで教師ラベルを合成しております。その結果、ポジティブ文章は1670文章、ネガティブ文章は1143文章、合計2813文章になりました。教師ラベルの合成方法詳細はこちらのブログをご覧ください。） pandasデータフレームにデータを格納した状態を確認してみましょう。 df = pd.read_csv(CFG.local_input_file_path) display(df)
A common question on SAS discussion forums is how to use SAS to generate random ID values. The use case is to generate a set of random strings to assign to patients in a clinical study. If you assign each patient a unique ID and delete the patients' names, you
Dedicated people, funding and data analytics can join forces to battle the opioid epidemic.
Attend this session during the SAS Explore event on Sept 27-29 or view the recording at your convenience. We will showcase the use of SAS Intelligent Decisioning, SAS Model Manager, and SAS Visual Analytics on the SAS Viya platform for a solution that helps mitigate inequitable credit decisions.
I recently showed how to represent positive integers in any base and gave examples of base 2 (binary), base 8 (octal), and base 16 (hexadecimal). One fun application is that you can use base 26 to associate a positive integer to every string of English characters. This article shows how
Thank you to Erica Blystone, LCSW, for this week's guest blog post. You can read more about Erica and her practice in the bio below. One of the most important decisions parents make during a divorce is the parenting plan (custody schedule). There are some guidelines that can make this easier.
こんにちは！SAS Institute Japanの堀内です。今回も自然言語処理について紹介いたします。 第１回目の投稿では、最近の自然言語処理の応用例とSAS社が携わった自然言語処理関連の実案件の概要を紹介しました。 第２回目の本投稿では実際にSASを使って日本語の文章を扱う自然言語処理の例を解説していきます。 テキストデータって何？ 自然言語処理を語る前に、自然言語処理が処理対象とするデータのことを知る必要があります。自然言語処理で扱われるデータはテキストデータと呼ばれています。ここからはテキストデータがどういうものか探っていきます。 テキストとは以下のようなものです。 「自然言語処理で扱われるデータはテキストデータと呼ばれています。本投稿ではテキストデータがどういうものか探っていきます。」 何の変哲もない日本語の文章です。日本語以外の言語で書かれた文章ももちろんテキストと呼ばれます。 ではテキストデータとは何でしょう？データと言うからには何らかの構造を持っていると考えます。例えば行と列が与えられたテーブルデータがわかりやすい例です。 テキストデータと呼ぶとき、テキストに何らかの構造を与えられたものを想起すると良いかと思います。上で挙げたサンプルのテキストをテキストデータに変換してみましょう。 ["自然言語処理で扱われるデータはテキストデータと呼ばれています。", "本投稿ではテキストデータがどういうものか探っていきます。"] これは句読点でテキストを区切り、リストに格納した例です。やりかたは他にもあります、 [["自然言語処理", "で", "扱われる", "データ", "は", "テキストデータ", "と", "呼ばれて", "います", "。"], ["本投稿", "では", "テキストデータ", "が", "どういうもの", "か", "探って", "いきます", "。"]] これは先ほどの例で２つのテキストに区切ったうえで、それぞれのテキストを更に単語ごとに区切って別々のリストに格納した例になります。これをテーブルデータのように整えると、 ID COL1 COL2 COL3 COL4 COL5 COL6 COL7 COL8 COL9 COL10 1 自然言語処理 で 扱われる
SAS' Gunce Walton introduces to you a new scoring capability, how it utilizes Deep Neural Networks (DNNs) and shares use cases with PROC DEEPCAUSAL.
An integer can be represented in many ways. This article shows how to represent a positive integer in any base b. The most common base is b=10, but other popular bases are b=2 (binary numbers), b=8 (octal), and b=16 (hexadecimal). Each base represents integers in different ways. Think of a
Students have returned to school and another year of education is underway. For some of them, though, the learning didn't stop over the summer. This dose of fun STEM education didn't require a classroom – just an iPad, a Sphero robot and the SAS® CodeSnaps app. Students work together to
The IEEE Visual Analytics Science and Technology (VAST) Challenge provides a great opportunity to validate our software against real-world scenarios using complex data sets. Not only do we learn from these projects, but we also send feedback to our development teams to further improve product capabilities for customers.
Historically Black Colleges and Universities (HBCUs) are vital to growing the next-generation workforce. At SAS, enabling and empowering HBCUs is an intentional component of our diversity, equity and inclusion strategy. We are committed to supporting and engaging with HBCUs from outreach and recruitment to supporting HBCU faculty, administration and research,
