Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
About Missing Values
Search
bk
August 09, 2019
Science
410
1
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
About Missing Values
bk
August 09, 2019
More Decks by bk
See All by bk
Befriending Kurtosis with R
bk_18
1
1k
tidy_rpart
bk_18
1
1.7k
dotdotdot_in_predict_function
bk_18
1
1.1k
Introduction_of_GoogleAnalytics_with_R
bk_18
2
1k
web scraping with polite package
bk_18
2
850
start-salesforce-with-r
bk_18
0
920
Missspell Detection
bk_18
1
170
Other Decks in Science
See All in Science
サンプル対応のない複数遺伝子発現プロファイルに対するテンソル分解型統合解析の要約
tagtag
PRO
0
250
データベース02: データベースの概念
trycycle
PRO
2
1.4k
社内で活躍できるデータサイエンティストになるために
aikinohara
1
160
機械学習 - K近傍法 & 機械学習のお作法
trycycle
PRO
1
1.6k
O(log n)-Approximation Algorithms for Bipartiteness Ratio
tasusu
0
170
(SIGBIO84) Inverse MSMD法による化合物部分構造プロファイリングと結合親和性推定
keisukeyanagisawa
PRO
0
110
水耕栽培を始める前に知っておきたい植物の科学
grow_design_lab
0
330
摂理と合理の肉体改造 — AI時代の減量を支える観測・制御・継続
kiyoshi
0
3.4k
チュートリアル:世界モデル
hf149
0
2.2k
AIPシンポジウム 2025年度 成果報告会 「因果推論チーム」
sshimizu2006
3
620
J-STAGE全文XML登載必須化について
xspa2012
0
1.5k
Bリーグのショットデータを活用した得点期待値モデルの構築 / Construction of expected points model using shot data of B.LEAGUE
konakalab
0
210
Featured
See All Featured
ラッコキーワード サービス紹介資料
rakko
1
4.7M
HTML-Aware ERB: The Path to Reactive Rendering @ RubyCon 2026, Rimini, Italy
marcoroth
4
550
Avoiding the “Bad Training, Faster” Trap in the Age of AI
tmiket
0
220
ピンチをチャンスに:未来をつくるプロダクトロードマップ #pmconf2020
aki_iinuma
128
56k
Building Better People: How to give real-time feedback that sticks.
wjessup
370
20k
Collaborative Software Design: How to facilitate domain modelling decisions
baasie
1
310
We Analyzed 250 Million AI Search Results: Here's What I Found
joshbly
1
1.9k
Building a Scalable Design System with Sketch
lauravandoore
463
34k
How to Align SEO within the Product Triangle To Get Buy-In & Support - #RIMC
aleyda
2
1.8k
JavaScript: Past, Present, and Future - NDC Porto 2020
reverentgeek
52
6.1k
RailsConf 2023
tenderlove
30
1.5k
What’s in a name? Adding method to the madness
productmarketing
PRO
24
4.2k
Transcript
ܽଛॲཧʹ͍ͭͯ dࣦΘΕͨΛٻΊͯd
࣍ 1. ܽଛͱ 2. ܽଛআڈ 3. ܽଛλΠϓ 4. ୯Ұೖ๏ 5.
ଟॏೖ๏ 6. ࠓճհ͠ͳ͔ͬͨͷ 7. ࢀߟจݙ
ܽଛͱ Missing Valueʢܽଛɺܽଌʣ In statistics, missing data, or missing values,
occur when no data value is stored for the variable in an observation. Missing data are a common occurrence and can have a significant effect on the conclusions that can be drawn from the data. ʢhttps://en.wikipedia.org/wiki/Missing_dataʣ
ܽଛ͕͋Δͱ Կ͕ࠔΔͷ͔ʁ ܽଛͱ
ܭࢉग़དྷͳ͍ Q,10, 20, ܽଛͷฏۉʁ ܽଛͱ > mean(c(10, 20, NA)) [1]
NA
Ͳ͏͢Δͷ͔ʁ ܽଛͱ
1. ফ͢ 2. ຒΊΔ ܽଛͱ
1. ফ͢ 2. ຒΊΔ 1. ফ͢ ܽଛͱ
ܽଛͷ͋ΔϨίʔυΛফ͢ ମॏ ੑผ 50 ঁ 70 உ 55 NA NA
உ ܽଛআڈ
ମॏ ੑผ 50 ঁ 70 உ 55 NA NA உ
ମॏ ੑผ 50 ঁ 70 உ ܽଛͷ͋ΔϨίʔυΛফ͢ ܽଛআڈ
ମॏ ੑผ 50 ঁ 70 உ 55 NA NA உ
ମॏ ੑผ 50 ঁ 70 உ ϦετϫΠζ๏ ܽଛͷ͋ΔϨίʔυΛফ͢ ܽଛআڈ
ফ͍͍ͯ͠ͷʁ 1. ফͯ͠ྑ͍߹ 2. ফͯ͠ବͳ߹ ܽଛআڈ
શʹϥϯμϜʹܽଛ ܽଛύλʔϯੑผ ମॏͱແؔ ܽଛআڈ
શʹϥϯμϜʹܽଛ ܽଛύλʔϯੑผ ମॏͱແؔ ফͯ͠ͳ͍ ͨͩ͠ɺޮԼ͕Δ ܽଛআڈ
؍ଌมʹґଘͯܽ͠ଛ ঁੑͷํ͕ଟܽ͘ଛ ܽଛআڈ
؍ଌมʹґଘͯܽ͠ଛ ফ͢ͱঁੑͷσʔλͷΈݮগ ภΔ ঁੑͷํ͕ଟܽ͘ଛ ܽଛআڈ
ܽଛมࣗମʹґଘͯܽ͠ଛ ମॏͷॏ͍ํ͕ଟ͘ ܽଛ ܽଛআڈ
ܽଛมࣗମʹґଘͯܽ͠ଛ ফ͢ͱମॏͷߴ͍σʔλ͕ݮগ ภΔ ମॏͷॏ͍ํ͕ଟ͘ ܽଛ ܽଛআڈ
‣ શʹϥϯμϜʹܽଛˠMCAR ʢMissing Completely At Randomʣ ‣ ؍ଌมʹґଘͯܽ͠ଛˠMAR ʢMissing At
Randomʣ ‣ ܽଛมࣗମʹґଘͯܽ͠ଛˠNMAR ʢNot Missing At Randomʣ ܽଛλΠϓ
‣ શʹϥϯμϜʹܽଛˠMCAR ʢMissing Completely At Randomʣ ‣ ؍ଌมʹґଘͯܽ͠ଛˠMAR ʢMissing At
Randomʣ ‣ ܽଛมࣗମʹґଘͯܽ͠ଛˠNMAR ʢNot Missing At Randomʣ ܽଛλΠϓ
‣ શʹϥϯμϜʹܽଛˠMCAR ʢMissing Completely At Randomʣ ‣ ؍ଌมʹґଘͯܽ͠ଛˠMAR ʢMissing At
Randomʣ ‣ ܽଛมࣗମʹґଘͯܽ͠ଛˠNMAR ʢNot Missing At Randomʣ ফͯ͠ྑ͍ ܽଛλΠϓ
‣ શʹϥϯμϜʹܽଛˠMCAR ʢMissing Completely At Randomʣ ‣ ؍ଌมʹґଘͯܽ͠ଛˠMAR ʢMissing At
Randomʣ ‣ ܽଛมࣗମʹґଘͯܽ͠ଛˠNMAR ʢNot Missing At Randomʣ ܽଛλΠϓ
‣ શʹϥϯμϜʹܽଛˠMCAR ʢMissing Completely At Randomʣ ‣ ؍ଌมʹґଘͯܽ͠ଛˠMAR ʢMissing At
Randomʣ ‣ ܽଛมࣗମʹґଘͯܽ͠ଛˠNMAR ʢNot Missing At Randomʣ ରॲࠔ ܽଛλΠϓ
‣ શʹϥϯμϜʹܽଛˠMCAR ʢMissing Completely At Randomʣ ‣ ؍ଌมʹґଘͯܽ͠ଛˠMAR ʢMissing At
Randomʣ ‣ ܽଛมࣗମʹґଘͯܽ͠ଛˠNMAR ʢNot Missing At Randomʣ ܽଛλΠϓ
‣ શʹϥϯμϜʹܽଛˠMCAR ʢMissing Completely At Randomʣ ‣ ؍ଌมʹґଘͯܽ͠ଛˠMAR ʢMissing At
Randomʣ ‣ ܽଛมࣗମʹґଘͯܽ͠ଛˠNMAR ʢNot Missing At Randomʣ ܽଛλΠϓ
1. ফ͢ 2. ຒΊΔ 1. ফ͢ 2. ຒΊΔ ୯Ұೖ๏
ͲΜͳͰຒΊΔͷ͔ʁ ୯Ұೖ๏
1. ฏۉʢฏۉೖ๏ʣ 2. ༧ଌʢ֬ఆతճؼೖ๏ʣ 3. ༧ଌ + ࠩʢ֬తճؼೖ๏ʣ + ୯Ұೖ๏
1. ฏۉʢฏۉೖ๏ʣ 2. ༧ଌʢ֬ఆతճؼೖ๏ʣ 3. ༧ଌ + ࠩʢ֬తճؼೖ๏ʣ + ୯Ұೖ๏
ฏۉΛܭࢉ͠ೖ ୯Ұೖ๏
ฏۉΛܭࢉ͠ೖ ฏۉೖ๏ ฏۉ ≒ உੑͷମॏͷฏۉ ୯Ұೖ๏
1. ฏۉʢฏۉೖ๏ʣ 2. ༧ଌʢ֬ఆతճؼೖ๏ʣ 3. ༧ଌ + ࠩʢ֬తճؼೖ๏ʣ + ୯Ұೖ๏
ܽଌΛ༧ଌ͢ΔϞσϧΛ࡞Δ *ิॿม ܽ ଛ ͷ ͋ Δ ม *ิॿม:ܽଛͷ༧ଌʹΘΕΔมɻඞͣ͠తมͷ༧ଌʹΘΕΔΘ͚Ͱͳ͍ɻ
୯Ұೖ๏
ܽଌΛ༧ଌ͢ΔϞσϧΛ࡞Δ ิॿม ܽ ଛ ͷ ͋ Δ ม ୯Ұೖ๏
ܽଌΛ༧ଌ͢ΔϞσϧΛ࡞Δ ܽ ଛ ͷ ͋ Δ ม ʢ֬ఆతʣ ճؼೖ๏
ิॿม ୯Ұೖ๏
ܽ ଛ ͷ ͋ Δ ม ิॿม ೖ͕શͯઢ্ʹ ୯Ұೖ๏
ܽ ଛ ͷ ͋ Δ ม ༧ଌͷޡࠩΛաখධՁ ิॿม ೖ͕શͯઢ্ʹ
୯Ұೖ๏
1. ฏۉʢฏۉೖ๏ʣ 2. ༧ଌʢ֬ఆతճؼೖ๏ʣ 3. ༧ଌ + ࠩʢ֬తճؼೖ๏ʣ 1. ฏۉʢฏۉೖ๏ʣ
2. ༧ଌʢ֬ఆతճؼೖ๏ʣ 3. ༧ଌ + ࠩʢ֬తճؼೖ๏ʣ + ୯Ұೖ๏
ೖϞσϧʹޡ߲ࠩΛՃ ܽ ଛ ͷ ͋ Δ ม ิॿม ޡ߲ࠩ
୯Ұೖ๏
ܽ ଛ ͷ ͋ Δ ม ิॿม ೖϞσϧʹޡ߲ࠩΛՃ Β͖ͭΛө
୯Ұೖ๏
ܽ ଛ ͷ ͋ Δ ม ิॿม ೖϞσϧʹޡ߲ࠩΛՃ ֬తճؼೖ๏
୯Ұೖ๏
ೖϞσϧͷޡ߲ࠩөग़དྷͨ ܽ ଛ ͷ ͋ Δ ม ิॿม ୯Ұೖ๏
ೖϞσϧͦͷͷͷෆ࣮֬ੑʁ ܽ ଛ ͷ ͋ Δ ม ิॿม ʁ
ʁ ʁ ୯Ұೖ๏
1ͭͷΛೖʢ୯Ұೖ๏ʣ ෳͷΛೖ ʢଟॏೖ๏ʣ ଟॏೖ๏
ೖ ੳ ౷߹ ෳͷೖΛਪఆ͠ෳͷೖࡁΈσʔλΛੜ ೖࡁΈσʔλΛ༻ͯ͠ਪఆ ਪఆΛ౷߹͠ɺ࠷ऴ݁Ռͱ͢Δ ଟॏೖ๏
ܽଛσʔλ ೖࡁΈσʔλ1 ೖࡁΈσʔλ2 ೖࡁΈσʔλ3 ੳ݁Ռ1 ੳ݁Ռ2 ੳ݁Ռ3 ࠷ऴ݁Ռ ೖ ੳ
౷߹ ଟॏೖ๏
ܽଛσʔλ ೖࡁΈσʔλ1 ೖࡁΈσʔλ2 ೖࡁΈσʔλ3 ੳ݁Ռ1 ੳ݁Ռ2 ੳ݁Ռ3 ࠷ऴ݁Ռ ೖ ੳ
౷߹ ଟॏೖ๏
‣ DA๏ : Data Augmentationʢσʔλ֦େ๏ʣ ‣ FCS๏ : Fully Conditional
Specificationʢ શ͖݅ࢦఆʣ ‣ EMB๏ : Expectation-Maximization with Bootstrapping ଟॏೖ๏
‣ ܽଛআڈɿϖΞϫΠζ๏ɺมআڈ ‣ ୯Ұೖ๏ɿൺೖ๏ɺϗοτσοΫ๏ɺίʔ ϧυσοΫ๏ɺLOCFɺNOCB ‣ ଟॏೖ๏ɿೖஅɺײੳ ‣ શใ࠷๏ ‣
LightGBMͳͲͷܽଛࣗಈॲཧ ࠓճհ͠ͳ͔ͬͨͷ
‣ ߴڮকٓ,ลඒஐࢠ, ܽଌσʔλॲཧ: RʹΑΔ୯Ұೖ๏ͱ ଟॏೖ๏ (౷ܭֶOne Point), ڞཱग़൛, 2017/12/9, 192ϖʔ
δ ‣ ܽଛ͕͋Δσʔλͷੳ, Sunny side up!, http:// norimune.net/1811 ‣ RͰ࣮ફʂܽଛσʔλੳೖʲ1ʳ, NHN TECHORUS Tech Blog, https://techblog.nhn-techorus.com/archives/6573 ‣ R ܽଛͷରԠʢmissing value treatmentʣ, ౷ܭֶͱӸֶͱ ࣌ʑɺॿڭੜ׆, http://jojoshin.hatenablog.com/entry/ 2017/02/03/220118 ࢀߟจݙ
ENJOY! A