데이터형

그룹화 변수, categorical형 데이터, dataset형 배열

Statistics and Machine Learning Toolbox™는 두 가지 추가 데이터형을 제공합니다. nominal 데이터형과 ordinal 데이터형을 사용하여 순서가 있는 비수치적 이산 데이터와 순서가 없는 비수치적 이산 데이터를 다룹니다. dataset 배열 데이터형을 사용하여 데이터형이 각각 다른 변수를 포함한 여러 변수를 단일 객체에 저장합니다. 그러나, 이러한 데이터형은 Statistics and Machine Learning Toolbox만의 고유한 데이터형입니다. 더 나은 제품 간 호환성을 제공하기 위해, 각각 MATLAB^®에서 제공되는 categorical 데이터형 또는 table 데이터형을 사용하십시오. 자세한 내용을 보려면 categorical형 배열 생성하기 항목과 테이블을 생성하고 테이블에 데이터 할당하기 항목을 참조하거나 테이블과 categorical형 배열 비디오를 참조하십시오.

함수

모두 확장

categorical형 데이터

`nominal`	(Not Recommended) Arrays for nominal data
`ordinal`	(Not Recommended) Arrays for ordinal data
`dummyvar`	Create dummy variables
`onehotencode`	Encode data labels into one-hot vectors
`onehotdecode`	Decode probability vectors into class labels
`gplotmatrix`	Matrix of scatter plots by group
`grp2idx`	Create index vector from grouping variable
`gscatter`	그룹별 산점도 플롯

dataset형 배열

`mat2dataset`	(Not Recommended) Convert matrix to dataset array
`cell2dataset`	(Not Recommended) Convert cell array to dataset array
`struct2dataset`	(Not Recommended) Convert structure array to dataset array
`table2dataset`	(Not Recommended) Convert table to dataset array
`dataset2cell`	(Not Recommended) Convert dataset array to cell array
`dataset2struct`	(Not Recommended) Convert dataset array to structure
`dataset2table`	Convert dataset array to table
`export`	(Not Recommended) Write dataset array to file
`ismissing`	(Not Recommended) Find dataset array elements with missing values
`join`	(Not Recommended) Merge dataset array observations

클래스

dataset (Not Recommended) Arrays for statistical data

도움말 항목

categorical형 데이터

Nominal and Ordinal Arrays
Nominal and ordinal arrays store data that have a finite set of discrete levels, which might or might not have a natural order.
Advantages of Using Nominal and Ordinal Arrays
Easily manipulate category levels, carry out statistical analysis, and reduce memory requirements.
그룹화 변수
그룹화 변수는 관측값을 그룹화하거나 분류하는 데 사용되는 유틸리티 변수입니다.
Dummy Variables
Dummy variables let you adapt categorical data for use in classification and regression analysis.
Other MATLAB Functions Supporting Nominal and Ordinal Arrays
Learn about MATLAB functions that support nominal and ordinal arrays.
Create Nominal and Ordinal Arrays
Create nominal and ordinal arrays using nominal and ordinal, respectively.
Categorize Numeric Data
Categorize numeric data into a categorical ordinal array using ordinal.
Change Category Labels
Change the labels for category levels in nominal or ordinal arrays using setlabels.
Add and Drop Category Levels
Add and drop levels from a nominal or ordinal array.
Merge Category Levels
Merge categories in a nominal or ordinal array using mergelevels.
Reorder Category Levels
Reorder the category levels in nominal or ordinal arrays using reorderlevels.
Sort Ordinal Arrays
Determine sorting order for ordinal arrays.
Plot Data Grouped by Category
Plot data grouped by the levels of a categorical variable.
Summary Statistics Grouped by Category
Compute summary statistics grouped by levels of a categorical variable.
Test Differences Between Category Means
Test for significant differences between category (group) means using a t-test, two-way ANOVA (analysis of variance), and ANOCOVA (analysis of covariance) analysis.
Index and Search Using Nominal and Ordinal Arrays
Index and search data by its category, or group.
Linear Regression with Categorical Covariates
Perform a regression with categorical covariates using categorical arrays and fitlm.

dataset형 배열

Dataset Arrays
Dataset arrays store data with heterogeneous types.
Create a Dataset Array from Workspace Variables
Create a dataset array from a numeric array or heterogeneous variables existing in the MATLAB workspace.
Create a Dataset Array from a File
Create a dataset array from the contents of a tab-delimited or a comma-separated text, or an Excel file.
Add and Delete Observations
Add and delete observations in a dataset array.
Add and Delete Variables
Add and delete variables in a dataset array.
dataset형 배열 변수의 데이터에 액세스하기
dataset형 배열 변수와 변수의 데이터를 사용해서 작업을 수행합니다.
Select Subsets of Observations
Select an observation or subset of observations from a dataset array.
Sort Observations in Dataset Arrays
Sort observations (rows) in a dataset array using the command line.
Merge Dataset Arrays
Merge dataset arrays using join.
Stack or Unstack Dataset Arrays
Reformat dataset arrays using stack and unstack.
Clean Messy and Missing Data
Find, clean, and delete observations with missing data in a dataset array.
Calculations on Dataset Arrays
Perform calculations on dataset arrays, including averaging and summarizing with a grouping variable.
dataset형 배열 내보내기
MATLAB 작업 공간에서 텍스트 또는 스프레드시트 파일로 dataset형 배열을 내보냅니다.
Dataset Arrays in the Variables Editor
The MATLAB Variables editor provides a convenient interface for viewing, modifying, and plotting dataset arrays.
Index and Search Dataset Arrays
Learn the many ways to index into dataset arrays.
Regression Using Dataset Arrays
This example shows how to perform linear and stepwise regression analyses using dataset arrays.

데이터형

함수

categorical형 데이터

dataset형 배열

클래스

도움말 항목

categorical형 데이터

dataset형 배열

관련 정보