F1: 87.47
Papers with Code · CC BY-SA 4.0
Time Series Analysis
Time Series Analysis is a statistical technique used to analyze and model time-based data. It is used in various fields such as finance, economics, and engineering to analyze patterns and trends in data over time. The goal of time series analysis is to identify the underlying patterns, trends, and seasonality in the data, and to use this information to make informed predictions about future values.
<span style="color:grey; opacity: 0.6">( Image credit: Autoregressive CNNs for Asynchronous Time Series )</span>
개요는 각 항목의 일부입니다. 위 탭에서 전체 기록을 페이지별로 탐색할 수 있습니다.
벤치마크
Papers with Code 아카이브의 데이터셋별 기록 예시입니다. 평가 조건과 지표 방향이 검증되지 않아 순위를 의미하지 않습니다.
Dataset기록된 모델 예시MetricPaperCode
데이터셋
154개논문
% Test Accuracy: 98.11
MAE: 0.1322
% Test Accuracy: 97.73
% Test Accuracy: 97.40
% Test Accuracy: 98.51
라이브러리
Papers with Code 리더보드 row에 연결된 구현 저장소입니다.
하위 태스크
TS
Time Series Forecasting
TS
Time Series Regression
TS
Time Series Anomaly Detection
TS
Time Series Clustering
TS
Time Series Prediction
MO
Model Optimization
DC
Data Compression
ST
Semi-supervised time series classification
TS
Time Series Alignment
TS
Time Series Averaging
TS
Time Series Denoising
TS
Time Series Streams