nlp-guild/non-linear-classification
收藏Hugging Face2023-04-14 更新2024-03-04 收录
下载链接：
https://hf-mirror.com/datasets/nlp-guild/non-linear-classification
下载链接
链接失效反馈官方服务：
资源简介：
---
license: mit
---
please use the following code to load data:
```python
# start data loading
!git lfs install
!git clone https://huggingface.co/datasets/nlp-guild/non-linear-classification
def load_dataset(path='dataset.npy'):
"""
:return:
f_and_xs: numpy array of size [sample_number, channels, sample_length]
label_0, label_1, label_2: one-hot encodes of size [sample_number, number_bins]
"""
r = np.load(path, allow_pickle=True).item()
f_and_xs = r['f_and_xs']
label_0 = r['l_0']
label_1 = r['l_1']
label_2 = r['l_2']
return f_and_xs, label_0, label_1, label_2
f_and_xs, label_0, label_1, label_2 = load_dataset('/content/Nonlinear-System-Identification-with-Deep-Learning/dataset.npy')
# end data loading
```
提供机构：
nlp-guild
原始信息汇总
数据集概述
数据集加载方法
数据集通过以下Python函数加载：
python def load_dataset(path=dataset.npy): """ :return: f_and_xs: numpy array of size [sample_number, channels, sample_length] label_0, label_1, label_2: one-hot encodes of size [sample_number, number_bins] """
r = np.load(path, allow_pickle=True).item()
f_and_xs = r[f_and_xs]
label_0 = r[l_0]
label_1 = r[l_1]
label_2 = r[l_2]
return f_and_xs, label_0, label_1, label_2
f_and_xs, label_0, label_1, label_2 = load_dataset(/content/Nonlinear-System-Identification-with-Deep-Learning/dataset.npy)
数据集内容
f_and_xs: numpy array，尺寸为 [sample_number, channels, sample_length]。label_0,label_1,label_2: one-hot编码，尺寸为 [sample_number, number_bins]。
