Jove
Visualize
お問い合わせ

関連する概念動画

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

383
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
383
Variability: Analysis01:11

Variability: Analysis

433
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
433
Randomized Experiments01:13

Randomized Experiments

8.8K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
8.8K
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

3.5K
Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
3.5K
Random Variables01:09

Random Variables

17.3K
A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
17.3K
Decision Making: P-value Method01:09

Decision Making: P-value Method

6.8K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
6.8K

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

Super greedy trees.

Artificial intelligence review·2026
Same author

Individual variable priority: a model-independent local gradient method for variable importance.

Artificial intelligence review·2025
Same author

Exploring molecular mechanism of Panlongqi Tablet (PLQT) against RA: Integrated network pharmacology, molecular docking and experiment validation.

International immunopharmacology·2024
Same author

Strategies for Achieving Carbon Neutrality: Dual-Atom Catalysts in Focus.

Small (Weinheim an der Bergstrasse, Germany)·2024
Same author

Spectrum-effect relationship between HPLC fingerprints and antioxidant activities of Bletilla striata.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences·2024
Same author

Discharge Communication and the Achievement of Lifestyle and Behavioral Changes Post-Stroke in the Transitions of Care Stroke Disparities Study.

American journal of lifestyle medicine·2024
Same journal

Spatial Coherence Loss: All Objects Matter in Salient and Camouflaged Object Detection.

Pattern recognition·2026
Same journal

LDM-Morph: Latent diffusion model guided deformable image registration.

Pattern recognition·2026
Same journal

A Deep Spatio-Temporal Architecture for Dynamic ECN Analysis with Granger Causality based Causal Discovery.

Pattern recognition·2025
Same journal

Medical image segmentation using dual-decoder mutual teaching with a mean teacher framework.

Pattern recognition·2025
Same journal

Multi-graph Graph matching for coronary artery semantic labeling in invasive coronary angiograms.

Pattern recognition·2025
Same journal

A graph transformer-based foundation model for brain functional connectivity network.

Pattern recognition·2025
関連記事をすべて見る
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する実験動画

Updated: Jan 13, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.9K

教師なし変数選択のための変数優先度

Lili Zhou1, Min Lu1, Hemant Ishwaran1

  • 1Division of Biostatistics, Miller School of Medicine, University of Miami.

Pattern recognition
|January 12, 2026
PubMed
まとめ
この要約は機械生成です。

この研究では、教師あり変数優先度(VarPro)を適応させることにより、新しい教師なし特徴選択法を導入する。このアプローチは、高次元データにおけるパフォーマンス向上のために、局所的な分類とラッソ回帰を使用する。

キーワード:
オートエンコーダーフォレストリリース領域信号変数s依存変数

さらに関連する動画

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.9K
Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

1.2K

関連する実験動画

Last Updated: Jan 13, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.9K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.9K
Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
03:37

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

1.2K

科学分野:

  • 機械学習
  • バイオインフォマティクス
  • データサイエンス

背景:

  • 教師なし特徴選択は、ラベル付きデータが利用できない場合に重要です。
  • 既存の方法には限界があり、新しいアプローチが必要とされています。
  • 高次元データは、情報量の多い特徴を特定する上で課題となります。

研究 の 目的:

  • 教師あり変数優先度(VarPro)フレームワークを教師なし設定に拡張すること。
  • ラベル付きデータなしで効果的な特徴選択のための方法を開発すること。
  • 高次元および複雑なデータシナリオでのパフォーマンスを向上させること。

主な方法:

  • 特徴選択を局所的な2クラス分類問題として再定式化すること。
  • 決定木ルールと領域メンバーシップを使用して暗黙的なクラスラベルを定義すること。
  • スパース性とノイズ削減のためにラッソベースの回帰を統合すること。

主要な成果:

  • 合成データで既存の教師なし特徴選択法を上回る一貫した改善を実証しました。
  • 実世界の生物学的および画像データセットで有効性を検証しました。
  • 既知のがん関連遺伝子を正常に回復し、肺がんのサブタイピングを改善しました。

結論:

  • 提案された方法は、教師なし特徴選択のための堅牢なソリューションを提供します。
  • 決定木から導出された暗黙的な教師あり学習は、特徴の特定を強化します。
  • このアプローチは、バイオインフォマティクスおよびデータ分析への応用が期待されます。