Multivariate time series classification pytorch lstm import torch import torch.nn as nn import torch.optim as optim import numpy as np from sklearn.model_selection import train_test_split # 生成示例数据 np.random.seed(0) n = 1000 # 样本数量 seq_len = 10 # 时间序列长度 n_features = 3 #...
Alonso C, Prieto O, Rodríguez J J, et al.Multivariate time series classification via stacking of univariate classifiers[M]//Okun O, Valentini G.Supervised and Unsupervised Ensemble Methods and Their Applications.New York:Springer, 2008:135-152....
时间序列 shapelet 是相对比较短的判别子序列,它不仅准确,而且可以解释单变量时间序列 (univariate time series UTS) 的分类问题。然而,现有的关于 shapelets 选择的工作不能应用于多元时间序列分类(multivariate time series classification MTSC),因为 MTSC 的候选 shapelets 可能来自不同长度的不同变量,因此无法直接比较...
the dimension shuffle operation reduces the computation time of training and inference without losing accuracy for time series classification problems. An ablation test is performed to show the performance of a model with the dimension shuffle operation is statistically the same as ...
一、背景 使用transdormer来进行多变量时间序列分类。提出了GTN网络。 二、模型 使用了双塔式 的transformer结构,这是因为在多变量的时间序列中,需要考虑...
Multivariate Time Series Classification with WEASEL+MUSE Multivariate time series (MTS) arise when multiple interconnected sensors record data over time. Dealing with this high-dimensional data is challenging for every classifier for at least two aspects: First, an MTS is not only characterize... P...
Early classificationFeature selectionMultivariate time series (MTS) classification is an important topic in time series data mining, and has attracted great interest in recent years. However, early classification on MTS data largely remains a challenging problem. To address this problem, we focus on ...
例如https://timeseriesai.github.io/tsai/models.rocket_pytorch.html 参考tsai的例子 multi-class-multivariate-classification https://timeseriesai.github.io/tsai/index.html#multi-class-multivariate-classification multivariate-regression https://timeseriesai.github.io/tsai/index.html#multivariate-regression...
Multivariate Time Series Classification with WEASEL+MUSEPatrick SchäferHumboldt University of BerlinBerlin, Germanypatrick.schaefer@informatik.hu-berlin.deUlf LeserHumboldt University of BerlinBerlin, Germanyleser@informatik.hu-berlin.deABSTRACTMultivariate time series (MTS) arise when multiple interconnected...
Most of existing data mining methods only considered single time series signal and worked in original dimension. Consequently, they performed poorly for extended dataset of patient records. The main challenge of ICU prediction is the data too big to be stored and processed in timely manner. The ...